The purpose of this document is to inform users of the accuracy of this data
product which has been determined by the CERES Team. This document briefly
summarizes key validation results, provides cautions where users might easily
misinterpret the data, provides helpful links to further information about the
data product, algorithms, and accuracy, gives information about planned data
improvements, and, finally, automates registration in order to keep users
informed of new validation results, cautions, or improved data sets as they
become available.
This document is a high-level summary and represents the minimum information
for scientific users of this data product. It is strongly suggested that
authors, researchers, and reviewers of research papers re-check this document
for the latest status before publication of any scientific papers using this
data product.
The quality of the CERES TRMM ES4 data is comparable to the quality of the
ERBE ERBS single-satellite S4 data in terms of monthly regional, zonal, and
global mean fluxes and scene identification. The major differences between
CERES/TRMM and ERBE/ERBS are the field of view resolution, the spectral
response of the instruments, the inclusion of rotating scanner plane data in
the CERES product, and the tropical-only coverage of CERES/TRMM.
Edition 2 significantly improves the quality of the unfiltered radiances
compared to Edition 1. Subsequent to release of ES4 Edition 1, it was revealed
that the unfiltering technique (basically the same algorithm used on ERBE) is
not the best choice for CERES due to the differences between the CERES and ERBE
spectral response functions. In the Edition 2 version of the ES4, this has been
corrected by using a new unfiltering algorithm outlined in Loeb et al,
"Determination of Unfiltered Radiances from the Clouds and the Earth's
Radiant Energy System (CERES) Instrument", J. Appl. Meteor.
[submitted 2000]). Also, updated spectral response functions were used in
determining the unfiltering coefficients. Otherwise, Edition 2 ES4s use the
same algorithms as was used in ES4 Edition 1 and ERBE (e.g. for determination
of filtered radiances, scene identification and radiance-to-flux conversion
etc.). We recommend that new users of the ES4 product use the Edition 2
version. For those who have already been using ES4 Edition 1, we provide
results of comparisons between the two versions in the section on Validation
Study Results.
This document discusses the ERBE-Like Science Product
[ES4] data set version Edition2. Additional information is in
the Description/Abstract
Guide. The CERES ES4 data product contains the "ERBE-like"
temporally and spatially averaged shortwave (SW) and longwave (LW)
top-of-the-atmosphere (TOA) fluxes derived from one month of CERES data from
the Tropical Rainfall Measuring Mission (TRMM) spacecraft. Instantaneous TOA
fluxes from the ES8 product have been spatially averaged on the same 2.5°
equal-angle grid used by the Earth Radiation Budget Experiment (ERBE). Temporal
interpolation algorithms identical to those used by ERBE have been applied to
produce daily, monthly-hourly, and monthly mean fluxes from the instantaneous
gridded data. The ES4 contains the temporally averaged values of TOA total-sky
LW, total-sky SW, clear-sky LW, and clear-sky SW flux, total-sky albedo and
clear-sky albedo for each 2.5° region observed during the month. In
addition, the 2.5° regional means have been combined to produce 5°
regional, 10° regional, 2.5° zonal, 5° zonal, 10° zonal, and
global mean fluxes.
When referring to a CERES data set, please include the satellite name and/or
the CERES instrument name, the data set version, and the data product. Multiple
files which are identical in all aspects of the filename except for the 6 digit
configuration code (see Collection Guide) differ little, if any,
scientifically. Users may, therefore, analyze data from the same
satellite/instrument, data set version, and data product without regard to
configuration code. This data set may be referred to as "CERES TRMM
Edition2 ES4."
The resolution of CERES TRMM is 10 km at nadir and the resolution of ERBE
ERBS is 40 km at nadir so that the surface area observed by ERBS is 16 times
larger than the area observed by TRMM.
The nominal scan mode for ERBE was crosstrack to provide good area coverage.
TRMM has two scan modes. The Fixed Azimuth Plane scan mode is similar to
ERBE. The Rotating Azimuth Plane (RAP) scan mode was added to TRMM to provide
angular coverage for construction of Angular Distribution Models (ADMs).
TRMM is in a low inclination (35°) orbit that precesses through all
local times in 46 days. The ERBS had an inclination of 57° and a
precessionary period of 72 days.
The longwave channel on ERBE was replaced by an 8 to 12 µm window
channel on TRMM.
The data rate on ERBS was 30 measurements per second. The data rate
on CERES is 100 measurements per second.
The ERBE ERBS S4 data product is a binary file of about 15 MB. The CERES
TRMM ES4 product is an HDF file of about 27 MB.
Edition 2 uses a different unfiltering algorithm than either Edition 1
or ERBE (Loeb et al., 2000).
There are several cautions the CERES Team notes regarding the use of
the ES4 TRMM Edition2 data:
CERES TRMM is observing more clear sky than ERBE due in part to the
difference in footprint size. The resolution of CERES TRMM is 10 km at nadir
and the resolution of ERBS is 40 km at nadir so that the surface area observed
by ERBS is 16 times larger than the area observed by TRMM. For the time period
of January through August, ~17% of ERBS footprints and ~28% of TRMM footprints
are classified as clear-sky. ERBS also observed about 17% overcast and TRMM
observed about 16% overcast. It is not fully understood why the overcast for
TRMM decreased instead of increasing as for clear sky. Overall the cloud
fraction was 46% for ERBS and 40% for TRMM.
The ERBE scene identification algorithm (MLE) in conjunction with the ERBE
angular distribution models (ADM) are known to erroneously produce albedo
growth from nadir to the limb. The ERBE ADMs are probably insufficiently
limb-darkened in longwave and insufficiently limb-brightened in shortwave. The
TRMM fluxes also have these biases with viewing angle.
The spectral response of the CERES shortwave and total channels differs
from that on ERBE at wavelengths below 1 micron. CERES uses silver mirrors,
which offer much more uniform spectral response from 0.4 µm to 100
µm than the ERBE aluminum mirrors, but are less responsive below 0.4
µm. A new spectral unfiltering algorithm has been developed and applied
to the CERES data. As a result, the CERES radiances are less sensitive to
spectral correction for land, desert, and cloudy scenes. The greatest impact of
this change is on SW fluxes, particularly for clear and partly cloudy ocean
scenes. Edition 2 clear-sky fluxes are lower than Edition 1 for clear ocean
scenes and slightly higher for land and desert scenes. Overall, Edition 2 CERES
clear-sky SW fluxes are 5-6% lower than ERBE ERBS fluxes for all scene types.
The TRMM spacecraft is in a 46-day precessing 35° orbit that is
designed to provide good coverage of the tropics. For regions poleward of
20°N and 20°S, the temporal sampling patterns are very different from
ERBS. In general, extratropical regions are viewed in daytime only during part
of the month and nighttime during the remainder. The typical ERBE sampling
pattern of alternating day and night observations only occurs in the tropics
with TRMM. Users should be aware that this temporal sampling can cause:
Large regional bias errors due to not sampling all local times during
a month. These errors can be reduced by a factor of 2 by using seasonal
means instead of monthly means.
Large errors in the modeling of diurnal variations of flux, particularly
for extratropical land and desert regions.
Insufficient coverage for calculating global means since there are no
data poleward of ±45°.
During 1998, the CERES TRMM instrument operated in a standard mode of 2
days of crosstrack scanning followed by 1 day of rotating azimuth plane (RAP)
scanning. Both the crosstrack and RAP data have been used in the computation
of CERES monthly mean fluxes. ERBE data were exclusively crosstrack.
The Earth may have real variations in longwave and shortwave radiation
properties between the ERBE time period and the CERES TRMM time period. The
major factors that we can note are:
The substantial and widespread increase in ocean temperature due to the
strong 1998 El Niño event that lies outside the range of conditions
encountered in the ERBE time period
Systematic changes in tropospheric water vapor between the 1998 El
Niño period and the ERBE period may have an influence on LW fluxes
Errors in scene identification due to the use of climatological values
for LW cloud thresholds that are inadequate for strong El Niño events.
Increased temperatures in the tropics will be interpreted as less cloud
which will introduce errors in the inversion from radiance to flux.
The possible darkening of some deserts owing to increased rainfall early
in 1998, again owing to El Niño
The potential changes in radiation over the tropics due to smoke from
fires in exceptionally dry forests, where the smoke may be confused with
clouds
The CERES Team has performed the following validation and quality assurance
processes on this data set:
Pre-Launch
The CERES ERBE-like operational code has been tested for consistency with
the historical ERBE algorithm. The CERES code was run using ERBE data as input.
Monthly mean SW and LW fluxes have been calculated that reproduce ERBE values
to better than 0.1%.
An error analysis of spatial averaging and temporal interpolation errors
has been performed using one month of 1-hourly, 4-km GOES data. In summary:
Spatial errors have been computed using simulated CERES footprints
constructed by convolving the GOES pixels with the CERES point spread
function. These footprints can be averaged on a grid and compared with
regional averages of the GOES pixels. Currently, results are only available
for the CERES 1.0° grid. For crosstrack data, the rms SW and LW flux
spatial gridding errors are 10.1 Wm-2 (5%) and 2.3 Wm-2
(1%), respectively, with no bias error for either. Errors for RAP data are
twice as large with SW errors of 23.1 Wm-2 and LW errors of 5.6
Wm-2. Currently, the best estimate for instantaneous gridding
error for the 2.5° ERBE-like grid is given by Stowe et al., (J. of Atmos.
& Ocean. Tech, 1994). For CERES-like footprints, Stowe et al. calculated
crosstrack errors of ~8.5 Wm-2 and ~1.3 Wm-2 for SW
and LW, respectively.
Temporal errors were calculated by temporally sampling GOES data
and comparing monthly means computed from these data with means from the
complete time series. SW and LW rms monthly mean errors are <11
Wm-2 (<12%) and <5 Wm-2 (<2%), respectively.
Bias errors for LW are < 0.5Wm-2. For SW, mean biases can be
±3 Wm-2 depending on the particular TRMM sampling pattern
for the month. The effects of the spatial gridding errors on monthly mean
errors are negligible in the LW and only increase monthly SW rms errors by
~0.5 Wm-2.
Post-Launch
The CERES ERBE-like data have been compared with ERBS non-scanner data for
verification of calibration. Tropical monthly mean ocean total-sky LW fluxes
have been averaged for all available months of ERBS scanner (1/85 - 12/89),
ERBS non-scanner (1/85 - 2/98), SCARAB scanner (3/94 - 2/95), and CERES scanner
(1/98 - 2/98) data. Scanner and non-scanner differences for each of the 3
scanners agree to < 1%. In addition, instantaneous CERES ERBE-like fluxes
have been compared with ERBS non-scanner data. Comparisons using data from
January through August 1998 have demonstrated agreement to within 0.1% for both
SW flux, 0.5% for nighttime LW flux, and 2.5% for daytime LW flux.
Directional models of the variation of albedo with solar zenith angle (SZA)
have been constructed using CERES TRMM and ERBE ERBS data for each of the 12
ERBE scene types. Comparisons of these models reveal no statistically
significant differences.
Six months of instantaneous rotating azimuth plane (RAP) and crosstrack
fluxes have been averaged as a function of SZA and scene type. These fluxes
agree to <1% in all cases with no statistically significant biases.
Seasonally averaged regional fluxes computed from crosstrack data alone
and from combined RAP and crosstrack data also show no systematic biases.
The first eight months of CERES ERBE-like data have been compared with
the historical ERBE ERBS scanner data from 1985-1989. The emphasis of this
study has been on comparisons of tropical mean fluxes (defined as the average
of all regions between 20°N and 20°S) in order to minimize temporal
sampling differences.
The main results include:
Total-sky LW flux - CERES LW fluxes are 3.5-8.8 Wm-2
(1.5-3.5%) higher than ERBE. The difference maximizes in February, which is
also the maximum of the 1998 El Niño event. The difference is minimized
in August when El Niño has essentially disappeared. As explained
above, a corresponding increse in total-sky LW flux from ERBE (1985-1989)
to 1998 is also seen in the ERBS non-scanner data.
Clear-sky LW flux - The CERES clear-sky LW fluxes are 1-3.
Wm-2 (0.2-1.0)% higher than ERBE. This difference also maximizes in
February and minimizes in August. The differences have been shown to be
consistent with variations in sea surface temperature and atmospheric humidity
associated with El Niño.
Total-sky SW flux - The difference between CERES and the 5-year mean
ERBE data varies between -0.6 and -5.0 Wm-2 (-0.6 and -5%). However,
the 2σ bound for the month-to-month temporal sampling variability of the
total-sky SW tropical mean for this time period is 5%. Seasonal (3-month) means
of SW flux reduce the impact of temporal sampling to a 2σ bound of 2.5%.
The CERES SW flux tropical seasonal means are lower than ERBE ERBS by 3-4%
which implies that there may be a real difference between ERBE and CERES SW
fluxes.
Clear-sky SW flux - In Edition 1, the difference between CERES and
ERBE in clear-sky SW flux varies with geographical scene type. The changes in
CERES spectral unfiltering have resulted in a more constant bias: CERES fluxes
are on the average 5.6%, 5.3%, and 6.1% lower than ERBE for ocean, land and
desert regions, respectively. The clear ocean difference is reduced to ~4% when
the CERES spatial resolution is reduced to simulate the ERBS field of view. The
land and desert differences are reduced only slightly by changing the spatial
resolution.
Scene identification - In general, CERES classifies more footprints
as clear than ERBE. This difference is also greatest in February with CERES
classifying 33% of the observations as clear, while ERBE classifies only 20% as
clear. The difference in July is decreased to 22% vs. 16%. Of the remaining
difference, about 2% can be attributed to the smaller CERES footprint size.
The CERES team expects to reprocess the S4 data product for ERBS, NOAA-9,
NOAA-10, and the ES4 data product for TRMM. The purpose of the reprocessing is
to generate a consistent, long-term climate record where advances in the data
calibration and processing will be incorporated to remove former errors. The
major contributions to reprocessing will be an improved set of Angular
Distribution Models based on CERES data and the MLE as the scene identifier.
Other improvements will be more accurate scanner offsets for NOAA-9 and NOAA-10,
correction of the low daytime longwave flux for NOAA-9, drift corrections, and
a possible resolution correction for CERES so that CERES and ERBS footprints
will be similar in size.
The CERES Team has gone to considerable trouble to remove major errors and
to verify the quality and accuracy of this data. Please provide a reference
to the following paper when you publish scientific results with the data:
Wielicki, B. A., B. R. Barkstrom, E. F. Harrison, R. B.
Lee III, G. L. Smith, and J. E. Cooper, 1996: Clouds and the Earth's Radiant
Energy System (CERES): An Earth Observing System Experiment,
Bull. Amer. Meteor. Soc., 77, 853-868.
When Langley DAAC data are used in a publication, we request the following
acknowledgment be included:
"These data were obtained from the NASA Langley Research
Center EOSDIS Distributed Active Archive Center."
The Langley Data Center requests a reprint of any published papers or reports
or a brief description of other uses (e.g., posters, oral presentations, etc.)
of data that we have distributed. This will help us determine the use of data
that we distribute, which is helpful in optimizing product development. It also
helps us to keep our product-related references current.
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Document Creation Date: June 22, 2000
Modification History: 12/20/2000 (non-science related update); 08/27/2001
(non-science related update); Dec 12, 2001
Most Recent Modification: December 12, 2001
