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CERES: Aqua Review NASA HQ, Aug 7, 2006

CERES: Aqua Review NASA HQ, Aug 7, 2006. CERES Level 1 Requirements: Products. "Two scanning broadband radiometers providing radiant flux at the Top of the Atmosphere"

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CERES: Aqua Review NASA HQ, Aug 7, 2006

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  1. CERES: Aqua Review NASA HQ, Aug 7, 2006

  2. 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.

  3. 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, <1% regional.

  4. Notable Recent CERES Science • Investigation of “Earthshine” albedo study (6 W m-2 increase in shortwave flux 2000-2003) versus CERES (< 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 <1% 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.

  5. 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: > 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

  6. 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

  7. 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

  8. Global Surface Temperature ChangeAR4 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.

  9. 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

  10. 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

  11. SW TOA Flux Interannual Variability: Tropical Ocean 0.21 Wm-2 Shows consistent calibration stability at < 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

  12. 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

  13. Using CERES to Determine Length of Climate Data Record Needed to Constrain Cloud Feedback 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 Half of Anthrop Forcing of 0.6 Wm-2 /decade

  14. 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.

  15. 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

  16. CERES Backup Slides HQ Aqua Review August 7, 2006

  17. TOA Flux Errors vs Time/Space Scale

  18. 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 < 0.1 < 0.1 < 0.1 • Angle Sampling (ADMs) + 0.2- 0.1+ 0.1 • Time Sampling (diurnal) < 0.2 < 0.2 < 0.2 • Reference Altitude (20km) 0.1 0.2 0.3 • Twilight SW Flux (= 0.25 Wm-2) < 0.1 0.0 < 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"

  19. Surface SW Flux Validation Noise Remarkable consistency for interannual anomalies 0.5 to 1 Wm-2

  20. Surface Downward Flux Errors: 20 - 40 Surface Sites

  21. 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

  22. 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

  23. 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)

  24. Climate Sensitivity vs Cloud FeedbackIPCC AR4 Models Climate sensitivity is essentially linear in cloud feedback Soden et al. 2006 J.Climate

  25. Cloud Feedback vs Cloud Radiative ForcingIPCC AR4 Models Cloud Feedback is essentially linear in cloud radiative forcing change Soden et al. 2006 J.Climate

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