USE OF AIRSAMSU DATA FOR WEATHER - PowerPoint PPT Presentation

Title: USE OF AIRSAMSU DATA FOR WEATHER


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• 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

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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