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USE OF AIRSAMSU DATA FOR WEATHER

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Title: USE OF AIRSAMSU DATA FOR WEATHER


1
  • USE OF AIRS/AMSU DATA FOR WEATHER
  • AND CLIMATE RESEARCH
  • Joel Susskind
  • University of Maryland
  • May 12, 2005

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USE OF AIRS/AMSU DATA FOR WEATHER AND CLIMATE
RESEARCH
  • AIRS/AMSU/HSB launched on EOS Aqua May 5, 2002
  • AIRS is a multi-detector array grating
    spectrometer
  • 2378 channels between 650 cm-1 and 2760 cm-1
  • Channel spacing (0.25 cm-1 -
    1.1 cm-1)
  • Resolving power (0.5
    cm-1 - 2.2 cm-1)
  • Footprint 13 km at nadir
  • 3 x 3 array within AMSU A footprint - collocated
    with HSB
  • One sounding produced per AMSU A footprint
  • HSB failed on February 5, 2003

3
OBJECTIVES OF AIRS/AMSU
  • Provide data to improve operational weather
    forecasting
  • Required global accuracy in up to 80 cloud
    cover
  • 1 K RMS error in 1 km layer mean tropospheric
    temperature
  • 20 RMS error in tropospheric 1 km layer
    precipitable water
  • Provide long-term global coverage of surface and
    atmospheric parameters
  • Monitor climate variability and trends
  • Study processes affecting climate change
  • Extend 25 year TOVS Pathfinder data set

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AIRS/AMSU PRODUCTS
  • Surface and Atmospheric Products - one set per
    FOR (45 km)
  • Sea/land skin temperature
  • Temperature profile T(p) to 1 mb
  • Water vapor profile q(p) to 100 mb
  • O3, CO, CH4 profiles
  • Cloud Cleared Radiances
  • Cloud Products - one set per FOV (13 km)
  • Effective cloud fraction for up to two
    cloud layers
  • is geometric fractional cloud cover
  • is cloud emissivity at 11 ?m
  • Cloud top pressure for up to two cloud
    layers
  • OLR
  • Computed using and retrieved
    parameters
  • Clear Sky OLR
  • Computed using retrieved parameters with
  • Each product has a quality flag

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PROPERTIES OF CHANNELS
  • effective average temperature
    within weighting function
  • At night radiance is weighted value
  • (brightness temperature) is weighted
    average between and
  • As decreases, decreases because
    see less of warm surface and more of
    . Also
  • decreases as peak of weighting function
    rises, but increases in stratosphere
  • increases brightness temperature,
    primarily for
  • Brightness temperatures can be higher than
    physical temperature

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OVERVIEW OF AIRS/AMSU RETRIEVAL METHODOLOGY
  • Physically based system
  • Independent of GCM except for surface pressure
  • Uses cloud cleared radiances to produce
    solution
  • represents what AIRS would have seen in
    the absence of clouds
  • Basic steps
  • Microwave product parameters solution agrees
    with AMSU A radiances
  • Initial cloud clearing using microwave product
    produces
  • AIRS regression guess parameters based on cloud
    cleared radiances
  • Update cloud clearing using AIRS regression
    guess parameters produces
  • Sequentially determine surface parameters, T(p),
    q(p), O3(p), CO(p), CH4(p), using
  • Apply quality control
  • Select retrieved state - coupled AIRS/AMSU or
    AMSU only retrieval parameters
  • Determine cloud parameters consistent with
    retrieved state and observed radiances
  • Compute OLR, CLR sky OLR from all parameters via
    radiative transfer

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QUALITY FLAGS
  • Order of increasing difficulty to pass
  • Stratospheric Temperature Test - temperature
    profile good above 200 mb
  • 90 and cloud clearing passes minimal
    quality control
  • Use coupled AIRS/AMSU retrieval state if
    Stratospheric Temperature Test
  • is passed
  • Constituent profile test
  • Slightly more stringent cloud clearing quality
    control
  • Mid-tropospheric Temperature Test - T(p) good
    above 3 km
  • Tighter quality control on cloud clearing and
    T(p) convergence
  • flagged good
  • Lower Troposphere Temperature Test - T(p) good
    above surface
  • SST test - for non frozen ocean only
  • 6) Tight SST test - for non frozen ocean only

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USE OF AIRS OBSERVATIONS FOR DATA ASSIMILATION
  • Could be (used by ECMWF, NCEP) or
    T(p),q(p) (used by Bob Atlas)
  • Accuracy of T(p),q(p) degrades slowly
    with increasing cloud fraction
  • There is a trade-off between accuracy and spatial
    coverage
  • ECMWF, NCEP uses radiances unaffected by clouds
  • Passes internal threshold tests
  • They should try assimilating clear column
    radiances unaffected by clouds
  • Bob Atlas assimilated T(p) for all levels flagged
    as good
  • Treats AIRS T(p) as radiosonde reports

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AIRS EXPERIMENTS WITH FVSSI
Global data assimilation system used fvSSI
fvGCM - Resolution 1x1.25 SSI (NCEP)
analysis-T62 Period of assimilation 1
January - 31 January, 2003 Experiments Control
All Conventional Data ATOVS Radiance
(NOAA-14, 15, 16) CTW SSM/I TPW SSM/I Wind
Speed QuikScat SBUV Ozone Contro
l AIRS Retrieved Temperature Profiles (Global,
passing level quality control) Forecasts 25
forecasts run every day beginning on January, 6
2003
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AIRS LEVEL 3 PRODUCTS
  • Different geophysical parameters are gridded
    according to different tests
  • Stratospheric Temperature Test
  • T(p) 200 mb and above
  • Constituent Profile Test
  • q(p), O3(p), CO(p) at all p
  • Mid-Tropospheric Temperature Test
  • T(p) beneath 200 mb, MSU2R/MSU4, land
    (including ice and coasts) surface skin
  • temperature (and emissivity)
  • Sea Surface Temperature Test
  • Non-frozen ocean surface skin temperature (and
    emissivity)
  • Cloud parameters, OLR and clear sky OLR use all
    AIRS cases

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Interannual Differences of T(P)

  • AIRS AIRS-ECMWF
    AIRS-TOVS
  • Jan 2004-2003
    Jan 2004-2003
    Jan 2004-2003
  • mean STD
    mean STD correlation mean
    STD correlation

Interannual Difference of
MSU2R/MSU4
AIRS
AIRS-Spencer-Christy
AIRS-TOVS
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DATA AVAILABILITY
  • Results shown are based on the AIRS Version 4.0
    algorithm
  • We (SRT) currently have results for January 2003
    and January, August, September 2004
  • Goddard DAAC began analyzing AIRS/AMSU data near
    real time April 1, 2004
  • DAAC is also processing backwards from March 31,
    2004 at 5 days per day
  • Level 1B (radiances), Level 2 (spot by spot
    retrievals), and Level 3 (gridded) data is
    available
  • Level 3 is 1x 1 daily, 8 day mean, and monthly
    mean
  • Ascending (130 pm local time) and descending
    (130 am local time) data are separate
  • To order data to go
  • http//daac.gsfc.nasa.gov/data/datapool/AIRS/inde
    x.html
  • Use collection 003 (Version 4.0)
  • Earlier DAAC products (collection 002) used AIRS
    Version 3.0
  • Do not use earlier results
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