NOAA-18 Instrument Calibration and Validation Briefing

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NOAA-18 Instrument Calibration and Validation
Briefing

• NOAA/NESDIS/Office of Research and Applications
• As of the Week of June 20, 2005
• For archived activities and latest news, please
  visit
• http//www.orbit.nesdis.noaa.gov/smcd/spb/n18calva
  l

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Weekly Highlights (June 20-24)

• HIRS
• On June 23, HIRS noise continues dropping.
  Several channels are now meeting the NEDN noise
  specification
• AMSU-A
• AMSU-A2 geolocation and co-registration errors
  are being confirmed
• AMSU scan bias symmetry characterization
• AMSU cloud liquid water
• AVHRR
• SST and aerosol diagnostics
• MHS
• Scan bias characterization
• Possible geolocation errors

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NOAA-18 Instrument Payload
We focus on these instruments

• AVHRR/4 Advanced Very High Resolution Radiometer
• HIRS/4 High Resolution Infrared Sounder
• AMSU-A Advanced Microwave Sounding Unit-A
• MHS Microwave Humidity Sounder
• SBUV/2 Solar Backscattered Ultraviolet Radiometer

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Calibration and Validation Legend

• PRT Platinum Resistance Thermometers
• NEDN/T Noise Equivalent Delta Radiance/Temperatur
  e
• ATOVS Advanced TIROS Operational Vertical
  Sounder (TOVS)
• TOAST Total Ozone Analysis using SBUV/2 and TOVS
• MSPPS Microwave Surface and Precipitation
  Product System
• NDVI Normalized Difference Vegetation Index
• SST Sea Surface Temperature
• UV Ultraviolet
• TPW Total Precipitable Water
• CLW Cloud Liquid Water

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ORA NOAA-18 Instrument Cal/Val Mission Goals

• Monitor and improve NOAA-18 instrument
  post-launch calibration
• Assess and quantify instrument noises though
  analyzing calibration target counts and channel
  measurements
• Monitor possible instrument anomaly and provide
  recommended solution
• Quantify satellite geolocation errors
• Characterize other biases in radiance and
  products such as cross-track asymmetry through
  forward modeling and inter-satellite calibration
• Validate NESDIS NOAA-18 products (ATOVS and
  MSPPS, TOAST, UV index, NDVI, SST) for
  operational implementation
• Provide early demonstration and assessments of
  NOAA-18 data for improving numerical weather
  prediction through JCSDA

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Our Team

• Mitch Goldberg ORA/SMCD Division Chief, -
  Management and Technical Oversight
• Fuzhong Weng ORA/SMCD/Sensor Physics Branch
  Chief and NOAA-18 cal/val team leader, instrument
  asymmetry and microwave products and algorithms,
  radiance bias assessments for NWP model
  applications
• Changyong Cao HIRS instrument calibration
• Fred Wu AVHRR VIS/IR instrument calibration
• Tsan Mo AMSU/MHS instrument calibration
• Jerry Sullivan AVHRR thermal channel
  calibration/ NDVI validation
• Tony Reale HIRS/AMSU/MHS sounding
  channel/products validation
• Mike Chalfant HIRS/AMSU/MHS sounding
  channel/products validation /geolocation
• Ralph Ferraro AMSU/MHS window channels/MSPPS
  products validation
• Larry Flynn SBUV product validation
• Tom Kleespies AMSU on-orbit verification
• Hank Drahos Sounding product validation
• Dan Tarpley AVHRR product NDVI monitoring
• John LeMashall Impacts assessments of NOAA-18
  data for NWP applications

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HIRS Cal/Val News

• HIRS noise continues to drop. Ch3, 11, and 12 now
  meet the NEDN noise spec. for the first time
• Channel 1 spaceview is still out of range most of
  the time
• See NEDN trending on http//www.orbit.nesdisnoaa.g
  ov/smcd/spb/multisensor/hirs/nedn

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NOAA-18/HIRS Sample Orbit (June 7,
2005) Brightness Temperature for 19 IR channels
ch1 ch2 ch3 ch4 ch5 ch6 ch7 ch8 ch9
ch10 ch11 ch12 ch13 ch14 ch15 ch16 ch17 ch18
Chs 1-12 longwave channels do not meet the spec
Ch 12 for water vapor
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NOAA-18/HIRS Sample Orbit (June 23, 2005)
Brightness temperature for all channels
ch1 ch2 ch3 ch4 ch5 ch6 ch7 ch8 ch9
ch10 ch11 ch12 ch13 ch14 ch15 ch16 ch17 ch18
Diminishing noises at all channels except ch1
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AMSU Cal/Val News

• AMSU-A geo-location and co-registration are being
  investigated by a few ORA scientists
• AMSU-A1 and A2 display some misalignment, and A1
  appears to be geolocated slight positive
  alongtrack and slight positive crosstrack
• AMSU-A2 appears to be geolocated negative along
  track and negative crosstrack
• Characterization of AMSU-A2 cross-track
  asymmetry results in a high quality of products
• The absolute asymmetry is characterized by the
  mean difference between simulations and
  observations at each beam position
• The relative asymmetry is characterized by the
  mean difference between pairwise left-right side
  brightness temperature

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NOAA-18 AMSU-A CHANNEL1 June 13
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NOAA-18 AMSU-A CHANNEL15 June 13
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AMSU Cloud Liquid Water vs. AVHHR Ch4
AMSU cloud liquid water is compared with AVHRR
image. AMSU cloud algorithm only retrieves
liquid water over oceans. It is seen that the
higher amount of liquid water is related to
strong convection corresponding to cold IR
temperature. This is a sanity check for initial
assessments of AMSU cloud algorithms
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AVHRR Cal/Val News

• AVHRR/3 IR data are used to produce global SST
  analysis. The products are demonstrated without
  excessive noises but with biases low (-0.35K to
  N17 and -0.45K to N16)
• AVHRR/3 channel 1 and 2 are used to produce
  aerosol optical depth and estimate the aerosol
  angstrom. It is shown that channel 1 is biased
  high by 6.9, and channel 2 is biased low by
  -1.4

Aerosol angstrom exponent (related to a ratio
of two AODs in AVHRR channel 1 and 2) is a very
sensitive indicator of AVHRR calibration.
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MHS Cal/Val News

• MHS scan bias characterization
• Earth scene brightness temperatures binned as
  function of scan position
• MHS scan asymmetry is characterized by the mean
  brightness temperatures differenced pairwise left
  right (ascending solid line, descending
  dashed
• Asymmetry from MHS window channels (89 and 157
  GHz) ambiguous ascending and descending
  portions of orbit have opposite signature,
  sounding channels show a slight bias (few tenth
  degree) with the right side being warmer
• MHS geolocation error
• The need for a possible  - 0.5 degree roll
  correction

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MHS Scan Biases and Asymmetry
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MHS Geolocation Errors
The composite images on the right quadrants view
the channel difference data from ascending and
descending nodes, showing only the main land /
sea features which only shows support for a
possible small roll correction in the ascending
pass