Data Product: ERBE-like Monthly Regional Averages (ES4)
Data Set: TRMM
Data Set Version: Edition1
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.
This document discusses the ERBE-Like Science Product
[ES4] data set version Edition1. 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
Edition1 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.
There are several cautions the CERES Team notes regarding the
use of the ES4 TRMM Edition1 data:
CERES TRMM is observing more clear sky than ERBE due in part to the
difference in footprint size. The resolution of 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 July, ~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 (Maximum Likelihood Estimator,
MLE) in conjunction with the ERBE angular distribution models (ADMs) 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 µm. CERES uses silver mirrors,
which offer a more uniform spectral response from 0.4 µm to 100 µm than
the ERBE aluminum mirrors, but are less responsive below 0.4 µm. The
spectral correction has therefore been modified from that on ERBE to
account for these differences. As a result, the CERES radiances are less
sensitive to spectral correction for land, desert, and cloudy scenes. The
ERBE radiances are less sensitive than CERES for clear-sky ocean. Further
studies are underway to evaluate the impact of spectral correction on the use
of the CERES clear ocean radiances and shortwave fluxes to study aerosol
radiative effects over ocean backgrounds. The current
spectral correction algorithm over ocean slightly overestimates unfiltered
SW radiance for large optical depths and slightly underestimates the SW
radiance for low optical depths. The net effect is likely to cause an overestimate
of aerosol radiative forcing of roughly 10%. In other words, if the
time-averaged SW radiative forcing for ocean aerosols is 2 Wm-2, the
current ERBE-Like spectral correction algorithm will cause the value to
incorrectly increase to 2.2 Wm-2. Improved spectral correction methods are
under development, and for clear ocean conditions are expected to reduce
this uncertainty by a factor of 5 to 10; however, the current ERBE-Like products
do not include this improvement.
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°.
The CERES TRMM instrument has 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 noted are:
The substantial and widespread increase in ocean temperature due to the
strong 1998 El Niño event 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. Preliminary comparisons using data from January and
February 1998 have demonstrated agreement to better than 1% for both LW
flux at night and SW flux. However, additional data are necessary to
establish agreement within CERES error limits due to limited sampling.
(ERBS non-scanner data from other 1998 months are expected to become
available late in 1998).
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 seven 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 5-10
Wm-2 (2-4%) higher than ERBE. The difference maximizes in
February, which is also the maximum of the 1998 El Niño event. The
difference is minimized in July when El Niño had essentially
disappeared. As explained above, a similar increase
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 1-3.5 Wm-2 (0.3-1.2%) higher than ERBE. This difference
also maximizes in February and minimizes in July. 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 +0.3 and -5 Wm-2 (+0.3 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%.
Therefore, the observed difference is within the temporal sampling error
limits.
Clear-sky SW flux - The difference
between CERES and ERBE in clear-sky SW flux varies with geographical scene
type. CERES fluxes are on the average 0.8 Wm-2 (1.8%),
4.1 Wm-2 (6.1%), and 7.3 Wm-2 (8.7%) lower
than ERBE for ocean, land and desert regions, respectively. In January, the
clear ocean difference can be reduced from -1.5 Wm-2 to
+0.2 Wm-2 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. The archived ES4
products were produced using the full resolution CERES data.
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 August is decreased to
25% vs 17%. Only 2-3% of the remaining difference 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: October 21, 1998
Modification History: 07/22/1999; 02/04/2000; 04/28/2000; 06/22/2000;
11/21/2000; 08/27/2001 (non-science related update)
Most Recent Modification: December 12, 2001