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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
        Weekly Highlights (June 20-24)

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

• SBUV/2 Solar Backscattered
  Ultraviolet Radiometer
     Calibration and Validation Legend

•   PRT: Platinum Resistance Thermometers
•   NEDN/T: Noise Equivalent Delta Radiance/Temperature

•   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
                  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
                               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
                    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
              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
              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
                  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
     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
                      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.
                       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
MHS Scan Biases and Asymmetry
                           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

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