CERES: Aqua Review

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CERES Aqua Review NASA HQ, Aug 7,
2006
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CERES Level 1 Requirements Products

• "Two scanning broadband radiometers providing
  radiant flux at the Top of the Atmosphere"
• One instrument for spatial scanning, one for new
  angular distribution models of earth's anisotropy
  fields. Successful on both.
• " Level 1 Radiances"
• Successful, now on Edition 2. Edition 3 in early
  2007.
• "Level 2 Instantaneous geophysical parameters
  (TOA Flux)
• Successful, including new angular models, now
  Ed2. Ed3 in late 07.
• "Level 3 Averaged geophysical parameters,
  possibly from mulitple instruments"
• Successful, ERBE-Like now Ed2, SRBAVG in Sept
  2006, AVG in 2007.
• "After launch ... data calibration and validation
  of standard data products"
• Successful, merged MODIS/CERES on Aqua, CERES on
  Aqua/Terranext is MODIS/CERES/geostationary/Terra
  /Aqua in 2006 2007.
• "As needed ... calibration updates, algorithmic
  improvements arising from improved validation,
  and for improving processing efficiencies"
• Underway for in orbit contamination correction (
  1), A-train.

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CERES Level 1 Requirements Products

• Data Processing and Testing Climate Data Record
  Focus
• Products merge global data from CERES crosstrack
  and rotating azimuth scanners, MODIS, GEOS-4
  weather assimilation, MATCH aerosol assimilation,
  microwave snow and sea-ice, 5 geostationary
  imagers. Up to 11 instruments on 7 spacecraft
  (including Terra).
• Products include levels 1 through 3 gridded
  products and include ERBE-like products as well
  as more advanced CERES products.
• TOA monthly biases at 1 to 2 W m-2 level (vs. 5
  W m-2 for ERBE), as required for climate change
  studies. Surface flux biases at 5-10 W m-2 (vs 20
  W m-2). Instrument stability at 0.1 to 0.5
  level.
• Aqua Angular Distribution Models (ADMs) developed
  from 2 years of data are now available. ADMs
  were developed with data from before the loss of
  the FM-4 SW channel. Aqua ADMs perform better
  than Terra ADMs, especially in the polar regions.
• Merged CERES and 3-hourly geosynchronous (GEO)
  data validated and released for Terra in spring
  2006 and scheduled for Aqua in fall 2006. Merged
  Terra/Aqua radiation diurnal cycles in 2007.
• CERES eliminates geo 5 calibration errors to
  0.1 global, lt1 regional.

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Notable Recent CERES Science

• Investigation of Earthshine albedo study (6 W
  m-2 increase in shortwave flux 2000-2003) versus
  CERES (lt 0.5 W m-2 decrease). Terra and Aqua
  albedo anomalies agree that there was a dip in
  global albedo of about 0.5 in 2003, but a return
  to values near 2000-2002 in 2004.
• CERES Terra albedo variations (2000-2005) show
  lt1 de-seasonalized variability and are highly
  correlated with MODIS-derived cloud fraction
  changes. Cloud fraction dominates but aerosol
  correlation suggests some aerosol indirect effect
  as well.
• CERES Global Net Radiation interannual anomalies
  agree to within 0.4 Wm-2 (1?) of independent
  ocean heat flux data.
• Six years of Terra/Aqua data show interannual
  variations in global radiation require 15-25
  years of overlapped 0.3/decade stability to
  constrain cloud feedback and climate sensitivity
  to /- 25.
• Radiative column closure in deep convection
  optically thick cloud limit over tropical ARM
  sites 2 consistency, TOA to Surface.
• 100,000 Terra and Aqua overpasses of 40 surface
  flux sites from equator to poles show consistency
  of 0.5 Wm-2 for interannual anomalies in SW, and
  1.0 Wm-2 in LW downward surface flux.

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What Didn't Work on CERES Aqua as Planned?

• CERES Mirror Attenuator Mosaic solar diffusers
  showed coating degradations in first two years on
  orbit. Weakened initial stability confirmation.
  Improve coatings on FM-5.
• CERES FM-4 SW channel failed March 30, 2005.
  Total and Window channels remain nominal.
  Obtained primary second instrument data
  requirement gt 2 years of rotating azimuth. But
  if CERES FM-3 fails, will need to derive CERES SW
  on FM-4 using MODIS/CERES merged at night for LW,
  and then apply in daytime for Total - LW SW.
• All CERES instruments have shown SW optics
  transmission loss when in rotating azimuth mode
  (1 to 2 over 5 years). Physical model in
  testing, Rev1 released to correct all-sky and
  clear-ocean. Edition 3 in 2007 will begin more
  rigorous correction for all scene types. All
  CERES instruments now in crosstrack to eliminate
  further changes.
• Data fusion more difficult than anticipated
  climate accuracy

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Next Steps

• Beta 3-hourly SYN/AVG products running off-line
  now, in production for Oct 23-27, 2006 Science
  Team meeting
• joint meeting with GERB at UKMO in Exeter.
• GERB Edition 1 30-minute time resolution for
  Meteosat view for broadband validation of diurnal
  cycles
• Cloud/Sfc/Atm Flux and cloud validation using
  CALIPSO/Cloudsat. Keys multilayer, polar,
  samples.
• Participating in GEWEX Radiative Flux Assessment
  of Decadal changes in surface and TOA radiation
  budget
• April 2003 - Oct 2005 Terra SRBAVG in beta
  testing Edition 2D out in fall. Aqua will
  follow.
• Edition 3 will correct SW/LW cal by scene type,
  improved cloud, aerosol, ADMs, GEOS 5, global
  net, Atmos fluxes, merged Terra/Aqua for advanced
  fusion data products.
• SW/HW conversions from SGI to clusters,
  automation

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Amount of change for a factor of 6 in climate
model sensitivity (2K to 12K for doubling CO2)
Cloud, Radiation, Sea Ice variables very sensitive
Dynamics variables not very sensitive
Weather dynamics, Climate energetics Need
Climate Change OSSEs, Climate Obs. Reqmts
Murphy et al. Nature, 2004
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Global Surface Temperature Change AR4 Climate
Models
Must determine climate sensitivity and
therefore cloud feedback well before
temperature signals show sensitivity can't
wait to after 2030

• Weak ability to distinguish climate sensitivity
  until after 2030
• Early temperature response similar because more
  sensitive climate models have a stronger ocean
  response delay.

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Cloud Radiative Forcing AR4 Climate Models

• Strong Positive
• Cloud Feedback
• Weak Positive
• Cloud Feedback

• - Noise likely dominated by ocean heat storage
  variability
• Cloud Feedback linear in change of cloud
  radiative forcing
• but because of clear sky changes even negative
  CRF change is a slight positive feedback.

B. Soden, Pers. Comm. 7/06
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CERES Net Radiation vs Global Ocean Heat Storage
We will need to carefully unscramble cloud
feedback and natural variability in ocean heat
storage a fusion of ocean/atmosphere data
Wong et al. 2006 J.Climate, in press
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SW TOA Flux Interannual Variability Tropical
Ocean
0.21 Wm-2
Shows consistent calibration stability at lt 0.3
Wm-2 per decade (95 conf) Unfortunately only
works for tropical mean ocean (nband vs bband
issues) Regional trends differ by 2 to -5
Wm-2/decade SeaWiFS vs CERES
Loeb et al. 2006 JGR, in press
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CERES Shortwave TOA Reflected Flux Changes Ties
to Changing Cloud Fraction
Unscrambling climate signal cause and effect
requires complete parameter set at climate
accuracy. For e.g. for forcing/response
energetics radiation, aerosol, cloud, land,
snow/ice, temperature, humidity, precipitation
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Using CERES to Determine Length of Climate Data
Record Needed to Constrain Cloud Feedback
Half of Anthrop Forcing of 0.6 Wm-2 /decade

• Given climate variability, 15 to 20 years is
  required to first detect climate trends at cloud
  feedback level with 90 confidence,
• and 18 to 25 years to constrain to /- 25 in
  climate sensitivity

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Future Issues

• Current IPCC AR4 climate model predictions/papers
  show
• global air sfc temperature change not
  discriminating next few decades for climate
  sensitivity (sensitive more ocean delay)
• uncertainty in climate sensitivity low clouds
  (Bony, GRL 2005)
• climate sensitivity linear in cloud radiative
  forcing (Soden and Held, Jclim 2006)
• CERES the only global cloud forcing observation
  demonstrated at the accuracy required (e.g. Loeb
  et al. 2006)
• NPOESS has just eliminated the CERES follow on
  sensor called ERBS.
• The last remaining CERES sensor (FM-5) is
  currently scheduled on NPOESS C2 in 2013/14 but
  gap risk is large greatly reduce if change to
  NPP in 2010.
• Cost estimates the same for NPP and NPOESS use of
  FM-5
• Would delay the most serious gap issue to 2015.
• Still need a plan for broadband global data
  2015-2025.

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The EOS Afternoon Satellite Constellation
(artwork by Alex McClung)
Key A-train Science Cloud, Aerosol and Aerosol
Indirect Effect Processes Largest IPCC Climate
Sensitivity and Anthropogenic Forcing
Uncertainties Unprecedented Data Fusion e.g.
NEWS CERES/CALIPSO/Cloudsat/MODIS Full vertical
profiles link aerosol to source, aerosol/cloud,
multilayer polar cloud
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CERES Backup Slides

• HQ Aqua Review
• August 7, 2006

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TOA Flux Errors vs Time/Space Scale
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Global Net Flux Balance Error Budget(out of
1365/ 4 341.25 Wm-2 SW LW)

• Error Source (white heating) SW LW Net
• Solar Constant (1361 vs 1365) 1.0 0.0 1.0
• Absolute Calibration 1.0 1.0 2.0
• Spectral Correction 0.5 0.3 0.8
• Spatial Sampling lt 0.1 lt 0.1 lt 0.1
• Angle Sampling (ADMs) 0.2 - 0.1 0.1
• Time Sampling (diurnal) lt 0.2 lt 0.2 lt 0.2
• Reference Altitude (20km) 0.1 0.2 0.3
• Twilight SW Flux ( 0.25 Wm-2) lt 0.1 0.0 lt 0.1
• Near Terminator SW Flux 0.7 0.0 0.7
• 3-D Cloud ?vis bias on ?(?o) 0.7
  0.0 0.7
• Ocean Heat Storage 0.4 -
  1.0
• Expected Global Net Range
  0 to 6.5
• CERES SRBAVG Ed2D Global Net 6.4
• Will provide community with advice for optimal
  global "closure"

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Surface SW Flux Validation Noise
Remarkable consistency for interannual anomalies
0.5 to 1 Wm-2
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Surface Downward Flux Errors 20 - 40 Surface
Sites
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Earthshine, ISCCP, CERES 2000 to 2004
Climate accuracy requirements are poorly
understood by the community recent Earthshine 6
changes were published in Science, causing much
confusion
Loeb et al., AGU 2005
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ISCCP FD versus CERES 2000 to 2004
Tropical 30S-30N
Global 90S-90N
Meteorological satellite climate data is not
accurate or stable enough to determine decadal
trends, but very useful for regional studies.
Loeb et al., AGU 2005
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Changing Cloud Forcing vs Vertical Velocity15
IPCC AR4 Climate Models 30S to 30N Ocean
Low Clouds Dominate Cloud Radiative
Forcing Changes (SW reflected flux) and Cloud
Feedback uncertainty
Change in Cloud Radiative Forcing/K Doubled CO2
Bony and Dufresne GRL, 2005
Vertical Velocity ( downward motion)
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Climate Sensitivity vs Cloud FeedbackIPCC AR4
Models
Climate sensitivity is essentially linear in
cloud feedback
Soden et al. 2006 J.Climate
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Cloud Feedback vs Cloud Radiative ForcingIPCC
AR4 Models
Cloud Feedback is essentially linear in cloud
radiative forcing change
Soden et al. 2006 J.Climate