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CERES EBAF Net Balancing
CERES and ERBE SW diurnal averaging comparison (1)
- Example Peruvian maritime stratus region, morning stratus clouds that burn off in the afternoon
- One would assume a greater albedo in the morning than in the afternoon
- Terra SSF1deg (ERBE interpolation) product overestimates the daily SW flux
- Aqua SSF1deg (ERBE interpolation) product underestimates the daily SW flux
- Terra SYN1deg (CERES interpolation) estimate is closer to the truth
CERES and ERBE SW diurnal averaging comparison (2)
- Difference the time interpolated SW fluxes based on Terra (10:30 equator local crossing time)
and Aqua (1:30PM) of December 2002
- Terra-only fluxes > Aqua-only fluxes over marine stratus regions (morning clouds)
- Aqua-only fluxes > Terra-only fluxes over land afternoon convection regions
- The SYN1deg have removed the Terra- Aqua sampling bias of the diurnal cycle
CERES and ERBE SW diurnal averaging comparison (1)
- Difference of the monthly regional means of CERES (SYN1deg) and ERBE (SSF1deg) temporal SW averaging
for Terra (10:30 AM sun-synchronous) December 2002
- Terra-SYN1deg monthly means overestimate the SW flux over maritime stratus and underestimate the afternoon convection regions
- Regional monthly differences can be > 20 Wm-2
- Global bias is - 1.0 Wm-2
CERES and ERBE LW diurnal averaging comparison (1)
- CERES-only (ERBE) LW land temporal interpolation uses a half-sine and constant nighttime fit if the daytime LW flux
is greater than the nighttime flux, to fill in 24 hourly time steps during the day
- CERES-only (ERBE) LW ocean and snow temporal interpolation uses linear interpolation, to fill in 24 hourly time steps during the day.
It is assumed that there are no LW diurnal cycles over clear-sky ocean and snow surfaces
- CERES/GEO LW temporal interpolation uses all CERES and 8 3-hourly (GMT) GEO derived BB fluxes normalized at coincident CERES/GEO
measurements to maintain CERES instrument calibration. All remaining hourly time steps are linearly interpolated between measurement times.
For nonpolar regions there are usually 2 CERES and 8 GEO measurements, almost half the hourly time steps
- For ERBE LW interpolation the land LW half-sin fit models the daytime heating, which assumes symmetry about noon.
- For ERBE LW interpolation, for a given daytime measurement, both a previous and following nighttime observation must be present to
apply half-sine fit. If the conditions are not met linear interpolation between measurements are used, causing erroneous flux estimates.
- It seems that the ERBE LW interpolation half-sine fit does not capture the daytime heating lag and nighttime cooling over land.
CERES and ERBE LW diurnal averaging comparison (2)
- Example Peruvian maritime stratus region, morning stratus clouds that burn off in the afternoon
- One would assume a greater albedo in the morning than in the afternoon
- ERBE LW interpolation would show symmetry about noon or no difference between 16:30 and 7:30 local time as the CERES interpolation does.
- The land afternoon convection regions (blue, for example Brazil), which are colder in the afternoon than morning and daytime heating thermal
lag regions (red, for example Sahara) indicating land is warmer near sunset rather than sunrise.
- Also the Peruvian maritime stratus regions are warmer in the afternoon indicating the clear-sky ocean is warmer than the morning cloud tops
- PM-AM differences can be ~ 30 Wm-2
CERES and ERBE LW diurnal averaging comparison (3)
- Terra-ERBE temporally interpolated means are similar to the CERES temporal averaging because the daytime and nighttime LW biases cancel out
- Global bias is +0.5 Wm-2
- CERES LW interpolation averaging reveals 3-hourly or 45° longitude striping due to discretization of the 3-hourly GEO measurements
Radiance view θ, solar θ0, and relative azimuth Φ angle definition
CERES vs ERBE view angle ADM comparison
Loeb, N.G., S. Kato, K. Louckachine, N. Manalo-Smith, D.R. Doelling; 2007: Angular Distribution
Models for Top-of-Atmosphere Radiative Flux Estimation from the Clouds and the Earth's Radiant Energy
System Instrument on the Terra Satellite Part II: Validation; J. Atmos. Oceanic Technol., 24, 564-584 Loeb et al.
- Ideally there would be a constant flux with respect to view angle
- Note the CERES ADM has almost removed the functionality with view angle, whereas ERBE-like is biased with view angle
- ERBE ADMs insufficiently limb-darken in the LW and insufficiently limb-brighten in SW.
CERES vs ERBE Clear-sky Scene Identification Comparison
- Note the cloud contamination in the ERBE-like clear-sky albedo product
- ERBElike scene identification uses 12 scene types to identify clear-sky footprints, whereas CERES uses ~600 scene types
Edition3 vs Edition2 Product Comparison Table
| Products | Edition3 | Edition2 |
|
| EBAF | EBAF | EBAF |
|
| SYN | SYN1deg-3Hour | SYN |
| SYN1deg-Day | SRBAVG (GEO) |
| SYN1deg-M3Hour | SRBAVG (GEO)/AVG/ZAVG |
| SYN1deg-Month | SRBAVG (GEO)/AVG/ZAVG |
|
| CRS | CRS | CRS |
| CRS1deg-Hour | FSW |
| CRS1deg-Day | N/A |
| CRS1deg-Month | N/A |
|
| SSF | SSF | SSF |
| SSF1deg-Hour | SFC |
| SSF1deg-Day | SRBAVG (nonGEO) |
| SSF1deg-MHour | SRBAVG (nonGEO) |
| SSF1deg-Month | SRBAVG (nonGEO) |
|
| ISCCP-D2like | ISCCP-D2like_M3Hour | ISCCP-D2like_Day/Nit* |
| ISCCP-D2like_Month | ISCCP-D2like_Day/Nit* |
|
| ERBElike | ES8 | ES8 |
| ES9 | ES9 |
| ES4 | ES4 |
*Day/Nit contains only the cloud properties whereas FlxDay/FlxNit contains both fluxes and cloud properties.
File Names Tables
Edition and netCDF Products / Lite Products
Edition2, Edition3, & netCDF File names
| Product |
Ed2 HDF Name |
Edition3 HDF Name |
Edition3 netCDF Name |
|
| EBAF |
EBAF | CERES_EBAF_TOA_Terra_Edition3A |
CERES_EBAF_Terra_Ed3A_xxxxx.nc |
|
| SYN |
SYNI |
CER_SYN1deg-1Hour_Terra-MODIS_Edition3A_013013.YYYYMMDD |
CERES_SYN1deg-1hour_Terra_Ed3A_xxxxx.nc |
| SYN |
CER_SYN1deg-3Hour_Terra-MODIS_Edition3A_013013.YYYYMMDD |
CERES_SYN1deg-3hour_Terra_Ed3A_xxxxx.nc |
SRBAVG
(GEO) |
CER_SYN1deg-Day_Terra-MODIS_Edition3A_013013.YYYYMMDD |
CERES_SYN1deg-Day_Terra_Ed3A_xxxxx.nc |
| CER_SYN1deg-M3Hour_Terra-MODIS_Edition3A_013013.YYYYMM |
CERES_SYN1deg-M3Hour_Terra_Ed3A_xxxxx.nc |
| AVG/ZAVG | CER_SYN1deg-Month_Terra-MODIS_Edition3A_013013.YYYYMM |
CERES_SYN1deg-Month_Terra_Ed3A_xxxxx.nc |
|
| CRS |
CRS |
CER_CRS_Terra-FM1-MODIS_Edition3A_013013.YYYYMMDDHH |
|
| FSW |
CER_CRS1deg-Hour_Terra-MODIS_Edition3A_013013.YYYYMMDD |
CERES_CRS1deg-Hour_Terra_Ed3A_xxxxx.nc |
| (new) |
CER_CRS1deg-Day_Terra-MODIS_Edition3A_013013.YYYYMMDD |
CERES_CRS1deg-Day_Terra_Ed3A_xxxxx.nc |
| (new) |
CER_CRS1deg-Month_Terra-MODIS_Edition3A_013013.YYYYMM |
CERES_CRS1deg-Month_Terra_Ed3A_xxxxx.nc |
|
| SSF |
SSF |
CER_SSF_Terra-FM1-MODIS_Edition3A_013013.YYYYMMDDHH |
|
| SFC | CER_SSF1deg-Hour_Terra-MODIS_Edition3A_013013.YYYYMMDD |
CERES_SSF1deg-Hour_Terra_Ed3A_xxxxx.nc |
SRBAVG
(nonGEO) |
CER_SSF1deg-Day_Terra-MODIS_Edition3A_013013.YYYYMMDD |
CERES_SSF1deg-Day_Terra_Ed3A_xxxxx.nc |
| CER_SSF1deg-Month_Terra-MODIS_Edition3A_013013.YYYYMM |
CERES_SSF1deg-Month_Terra_Ed3A_xxxxx.nc |
|
| ISCCP-D2like |
ISCCP-D2like |
CER_ISCCP-D2like-FlxDay_Terra-MODIS_Edition3A_013013.YYYYMM |
CERES_ISCCP-D2like-FluxDay_Terra_Ed3A_xxxxxx.nc |
| CER_ISCCP-D2like-FlxNit_Terra-MODIS_Edition3A_013013.YYYYMM |
CERES_ISCCP-D2like-FluxNit_Terra_Ed3A_xxxxx.nc |
| CER_ISCCP-D2like-GEO_Edition3A_013013.YYYYMM |
CERES_ISCCP-D2like-GEO_Ed3A_xxxxx.nc |
| CER_ISCCP-D2like-Mrg_GEO-Terra_Aqua-Edition3A_013013.YYYYMM |
CERES_ISCCP-D2like-Merge_Ed3A_xxxxx.nc |
|
| FLASHFlux |
FLASH_SSF | FLASH_SSF_Terra-FM1-MODIS_Version2G_008019.YYYYMMDDHH |
FLASH_SSF_Terra_Version2G_xxxxxx.nc |
| FLASH_TISA | FLASH_SSF1deg-Day_Terra+Aqua_Version2G_013013.YYYYMMDD |
FLASH_SSF1deg-Day_Terra+Aqua_Version2G_xxxxx.nc |
| FLASH_SSF1deg-Month_Terra+Aqua_Version2G_013013.YYYYMM |
FLASH_SSF1deg-Month_Terra+Aqua_Version2G_xxxxxx.nc |
|
| ERBElike |
ERBElike | CER_ES4_Terra-FM1_Edition3_013013.YYYYMM |
CERES_ES4_Terra_Ed3_xxxxx.nc |
| CER_ES8_Terra-FM1_Edition3_013013.YYYYMMDD | |
** Last update April 2010
Lite Level3&4 Edition2.6 Product Filenames
| Edition2 HDF Name |
Edition2.6 HDF Name |
Edition2.6 netCDF Name |
| EBAF | CERES_EBAF-TOA-Terra_Ed2.5_xxxxx.nc | CERES_EBAF-TOA-Terra_Ed2.5_Subset_xxxxx.nc |
| SYN | CER_SYN1deg-Day-lite_Terra_Ed2.5_xxxxx.hdf | CERES_SYN1deg-Day-lite_Terra_Ed2.5_Subset_xxxxx.nc |
| CER_SYN1deg-Month-lite_Terra_Ed2.5_xxxxx.hdf | CERES_SYN1deg-Month-lite_Terra_Ed2.5_Subset_xxxxx.nc |
| SSF | CER_SSF1deg-Day-lite_Terra_Ed2.5_xxxxx.hdf | CERES_SSF1deg-Day-lite_Terra_Ed2.5_Subset_xxxxxx.nc |
| CER_SSF1deg-Month-lite_Terra_Ed2.5_xxxxx.hdf | CERES_SSF1deg-Month-lite_Terra_Ed2.5_Subset_xxxxxx.nc |
** Last update April 2010
Level Descriptions
- Level 3B: Level 3 data products that are adjusted within their range of
uncertainty so as to satisfy known constraints on the climate system
(e.g., consistency between average global net TOA flux imbalance and ocean heat storage).
- Level 3: Data products are the radiative fluxes and cloud properties that are
spatially averaged into uniform regional and zonal grids and globally and also
temporally averaged into daily, monthly hourly, or monthly means.
- Level 2: Data products are derived geophysical variables at the CERES footprint
resolution as the Level 1B source data. They include the Level 1B parameters,
along with the retrieved or computed geophysical variables such as radiative
broadband fluxes and their associated MODIS cloud properties.
- Level 1B: Data products are processed to sensor units. The BDS product contains
CERES footprint filtered broadband radiances, geolocation and viewing geometry,
Sun geometry, satellite position and velocity, and all raw engineering and status
data from the instrument.
EBAF Net Balance
- CERES product TOA fluxes have a positive net imbalance, due mainly to the CERES instrument absolute calibration
- The CERES EBAF-TOA
product was designed for climate modelers that need a net imbalance constrained to the ocean heat storage term
(Hansen et al. 2005)
- CERES also uses the observed SORCE incoming solar fluxes
(Koop et al. 2005),
which has solar constant of 1361.0
- CERES performed a flux uncertainty analysis and determined that the CERES instrument calibration
was the largest uncertainty at 2% for the SW and 1% for LW.
- More information can be found in the
EBAF-TOA Data Quality Summary (DQS)
Comparison of ERBElike, SSF1deg, SYN1deg, and EBAF fluxes
TOA fluxes (Wm-2)
Mar00-Feb04 |
ERBElike
Edition2 |
SSF1deg
Edition2 |
SYN1deg
Edition2 |
EBAF
Edition2 |
| Incoming Solar | 341.3 | 341.3 | 341.3 | 340.0 |
| OLR | 239.0 | 237.7 | 237.2 | 239.7 |
| SW | 98.3 | 96.6 | 97.7 | 99.5 |
| Net | 4.0 | 7.0 | 6.0 | 0.85 |
CERES Net flux uncertainty analysis
Net flux sensitivity (αi), standard deviation of error (σi),
maximum likelihood error (xi), and error effect on net TOA flux.
| Parameter |
Net TOA Flux
sensitivity, αi (W/m2/%) |
2σ uncertainty, δi (%) |
Maximum Likelihood
solution, xi (%) |
TOA Flux
adjustment (W/m2) |
| SW gain | -0.977 | 2.0 | 1.6 | 1.57 |
| LW gain | -2.37 | 1.0 | 0.972 | 2.3 |
| Unfiltered SW | -0.977 | 0.5 | 0.105 | 0.1 |
| Unfiltered LW(N) | -1.19 | 0.2 | 0.022 | 0.03 |
| Unfiltered LW(D) | -1.19 | 0.38 | 0.07 | 0.08 |
| SW radiance to flux | -0.977 | 0.20 | 0.017 | 0.02 |
| LW radiance to flux | -2.37 | 0.13 | 0.016 | 0.04 |
| Time-averaging SW | -0.977 | 0.30 | 0.038 | 0.04 |
| Time-averaging LW | -2.37 | 0.13 | 0.016 | 0.04 |
| Reference Level, SW | -0.977 | 0.10 | 0.004 | 0.00 |
| Reference Level, LW | -2.37 | 0.08 | 0.007 | 0.02 |
| Incoming Solar | 3.40 | 0.06 | -0.005 | -0.02 |
| Total SW | | | | 1.7 |
| Total LW | | | | 2.5 |
| Total Net | | | | -4.2 |
- Note the SW and LW gains or instrument absolute calibration have
the highest uncertainty and largest corresponding TOA flux adjustment
CERES Earth's Radiation Budget
- For the Earth to remain in balance the energy coming into and leaving the Earth must equal.
- The CERES absolute instrument calibration currently does not have zero net balance and must be
adjusted to balance the Earth's energy budget.
- After the EBAF adjustment the CERES fluxes may be used in climate models for climate model evaluation,
estimating the Earth's global mean energy budget and to infer meridional heat transport.
CERES Data Product Information
Title: Constrained least-squares image restoration filters for sampled image data
Publication: Proc. SPIE, Vol. 2028, 177 (1993); doi:10.1117/12.158634
Authors: Hazra, R., S. Park, G. L. Smith, and S. E. Reichenbach
Title: Documentation and validation of the Goddard Earth Observing System (GEOS) Data Assimilation System - Version 4.
NASA Technical Report Series on Global Modeling and Data Assimilation
Publication: M. Journal of Suarez, Editor, NASA/TM-2005-104606, 26 pp., 2005
Authors: Bloom, S., A. da Silva, and D. Dee
Title: Simulating aerosols using a chemical transport model with assimilation of satellite aerosol retrievals,
Methodology for INDOEX.
Publication: Journal of Geophys. Res., 106, 7313-7336., 2001
Authors: Collins, W. D., P. J. Rasch, B. E. Eaton, B. V. Khattatov, J.-F. Lamarque, and C. S. Zender
Title: Seasonal variation of surface radiation budget derived from ISCCP-C1 data.
Publication: Journal of Geophysical Research, Vol. 97, 15 741-15 760., 1992
Authors: Darnell, W. L., W. F. Staylor, S. K. Gupta, N. A. Ritchey, and A. C. Wilber
Title: A Parameterization for Longwave Surface Radiation from Satellite Data: Recent Improvements.
Publication: Journal of Applied Meteorology, Vol. 31, No. 12, 1992, pp. 1361-1367.
Authors: Gupta, S. K., Darnell, W. L., and Wilber, A. C.
Title: The Langley Parameterized Shortwave Algorithm (LPSA) for surface radiation budget studies (Version1.0).
Publication: NASA/TP-2001-211272, 31 pp., 2001
Authors: Gupta, S. K., D. P. Kratz, P. W. Stackhouse Jr., and A. C. Wilber
Title: Improvement of Surface Longwave Flux Algorithms Used in CERES Processing.
Publication: Journal of Applied Meteorology and Climatology, Vol. 49, No. 7, 2010, pp. 1,579 - 1,589.
Authors: S. K. Gupta, D. P. Kratz, P. W. Stackhouse, Jr., A. C. Wilber, T. Zhang, and V. E. Sothcott
Title: Earth's energy imbalance: Confirmation and implications.
Publication: Science, 308, 1431-1435., 2005
Authors: Hansen, J., and co-authors
Title: Aerosol Retrievals from the Multiyear Multisatellite AVHRR Pathfinder Atmosphere (PATMOS) Dataset
for Correcting Remotely Sensed Sea Surface Temperatures.
Publication: Journal of Atmospheric and Oceanic Technology, Vol. 19, 1986-2008., 2002
Authors: Ignatov, A., and N. R. Nalli
Title: Two MODIS Aerosol Products over Ocean on the Terra and Aqua CERES SSF Datasets.
Publication: Journal of the Atmospheric Sciences, Vol. 62, 1008-1031, 2005
Authors: Ignatov, A., P. Minnis, N.G. Loeb, B.A. Wielicki, W.F. Miller, S. Sun-Mack, D. Tanré, L. Remer, I. Laszlo, and E. Geier
Title: Estimation of Longwave Surface Radiation Budget.
Publication: Clouds and the Earth's Radiant Energy System (CERES) Algorithm Theoretical Basis Document, CERES (Subsystem 4.6.2), Release 2.2. June 2, 1997
Authors: Inamdar, A. K. and Ramanathan, V.
Title: Total Irradiance Monitor Design and On-Orbit Functionality.
Publication: SPIE Proc. 5171-4, 2003, pp. 14-25.
Authors: Kopp, G., Lawrence, G., and Rottman, G.
Title: The Total Irradiance Monitor (TIM): Science Results.
Publication: Solar Physics, 230, 129-140., 2005
Authors: Kopp, G., G. Lawrence, and G. Rottman
Title: Validation of the CERES Edition 2B Surface-Only Flux Algorithms.
Publication: Journal of Applied Meteorology and Climatology, DOI: 10.1175/2009JAMC2246.1, 2009
Authors: Kratz, D.P., S. K. Gupta, A. C. Wilber, V. E. Sothcott
Title: Estimation of SW Flux Absorbed at the Surface from TOA Reflected Flux.
Publication: Journal of Climate, Vol. 6, No. 2, 1993, pp. 317-330.
Authors: Li, Z., Leighton, H. G., Masuda, K., and Takashima, T.
Title: Determination of unfiltered radiances from the Clouds and the Earth's Radiant Energy System (CERES) instrument.
Publication: Journal of Appl. Meteor, 40, 822-835, 2001
Authors: Loeb, N.G., K.J. Priestley, D.P. Kratz, E.B. Geier, R.N. Green, B.A. Wielicki, P. O'R. Hinton, and S.K. Nolan
Title: Angular distribution models for top-of-atmosphere radiative flux estimation from the
Clouds and the Earth's Radiant Energy System instrument on the Terra satellite. Part I: Methodology.
Publication: Journal of Atmospheric and Oceanic Technology, Vol. 22, 338-351., 2005
Authors: Loeb, N. G., S. Kato, K. Loukachine, and N. Manalo-Smith
Title: Angular distribution models for top-of-atmosphere radiative flux estimation from the
Clouds and the Earth's Radiant Energy System instrument on the Terra satellite. Part II: Validation.
Publication: Journal of Atmospheric and Oceanic Technology, Vol. 24, 564-584., 2007
Authors: Loeb, N. G., S. Kato, K. Loukachine, N. Manalo-Smith, and D. R. Doelling
Title: CERES Edition-2 Cloud property retrievals using TRMM VIRS and Terra and Aqua MODIS data, Part I: Algorithms.
Publication: Submitted to IEEE Transactions on Geoscience and Remote Sensing, 2009
Authors: Minnis, P., S.Sun-Mack, D.F. Young, P.W. Heck, D.P. Garber, Y.C. Chen, D.A. Spangenberg, R.F. Arduini, Q.Z. Trepte,
W. L. Smith Jr., J.K. Ayers, S.C.Gibson, W.F. Miller, V. Chakrapani, Y. Takano, K.N. Liou, Y. Xie
Title: Updated daily. Near-Real-Time SSM/I-SSMIS EASE-Grid Daily Global Ice Concentration and Snow Extent, [1998-present].
Publication: Boulder, Colorado USA: National Snow and Ice Data Center. Digital media. 1998
Authors: Nolin, A., R. L. Armstrong, and J. Maslanik
Title: Algorithm for Remote Sensing of Tropospheric Aerosol from MODIS for Collection 005:
Revision 2 Products: 04_L2, ATML2, 08_D3, 08_E3, 08_M3.
Publication:
Authors: Remer, Tanré, Kaufman, Levy, & Mattoo
Title: Angular Radiation Models for Earth-Atmosphere System: Volume I - Shortwave Radiation.
Publication: NASA RP 1184, 144 pp., July 1988.
Authors: Suttles, J. T., Green, R. N., Minnis, P., Smith, G. L., Staylor, W. F., Wielicki, B. A.,
Walker, I. J., Young, D. F., Taylor, V. R., and Stowe, L. L.
Title: Angular Radiation Models for Earth-Atmosphere System: Volume II - Longwave Radiation.
Publication: NASA RP 1184, 144 pp., July 1989.
Authors: Suttles, J. T., Green, R. N., Minnis, P., Smith, G. L., Staylor, W. F., Wielicki, B. A.,
Walker, I. J., Young, D. F., Taylor, V. R., and Stowe, L. L.
Title: Temporal Interpolation Methods for the Clouds and Earth's Radiant Energy System (CERES) Experiment.
Publication: Journal of Applied Meteorology, 37, pp. 572-590, 1998.
Authors: Young, D. F., P. Minnis. D. R. Doelling, G. G. Gibson, and T. Wong
Title: SMOBA: A 3-dimensional daily ozone analysis using SBUV and TOVS measurements, 1997.
Publication:
Authors: Yang, S. K., S. Zhou, and A. J. Miller
Title: SMOBA: A 3-dimensional daily ozone analysis using SBUV/2 and TOVS measurements, 2000.
Publication:
Climate Prediction Center Abstract 
Authors: Yang, S. K., S. Zhou, and A. J. Miller
Title: Algorithm-development strategies for retrieving the downwelling longwave flux at the Earth's surface.
Publication: Journal of Geophysical Research, Vol. 106, pp. 12477-12488, 2001
Authors: Zhou Y. and R. D. Cess
Title: An improved algorithm for retrieving surface downwelling longwave radiation from satellite measurements.
Publication: Journal of Geophysical Research, Vol. 112, D15102, doi:10.1029/2006JD008159, 2007
Authors: Zhou Y., D. P. Kratz, A. C. Wilber, S. K. Gupta, and R. D. Cess
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