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G. Louis Smith
and
David R. Doelling

Abstract

The effects of the earth’s oblateness on computation of its radiation budget from satellite measurements are evaluated. For the Clouds and the Earth’s Radiant Energy System (CERES) data processing, geolocations of the measurements are computed in terms of the geodetic coordinate system. Using this system accounts for oblateness in the computed solar zenith angle and length of day. The geodetic and geocentric latitudes are equal at the equator and poles but differ by a maximum of 0.2° at 45° latitude. The area of each region and zone is affected by oblateness as compared to geocentric coordinates, decreasing from zero at the equator to 1.5% at the poles. The global area receiving solar radiation is calculated using the equatorial and polar axes. This area varies with solar declination by 0.0005. For radiation budget computations, the earth oblateness effects are shown to be small compared to error sources of measuring or modeling.

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Pamela E. Mlynczak
,
G. Louis Smith
, and
David R. Doelling

Abstract

The seasonal cycle of the Earth radiation budget is investigated by use of data from the Clouds and the Earth’s Radiant Energy System (CERES). Monthly mean maps of reflected solar flux and Earth-emitted flux on a 1° equal-angle grid are used for the study. The seasonal cycles of absorbed solar radiation (ASR), outgoing longwave radiation (OLR), and net radiation are described by use of principal components for the time variations, for which the corresponding geographic variations are the empirical orthogonal functions. Earth’s surface is partitioned into land and ocean for the analysis. The first principal component describes more than 95% of the variance in the seasonal cycle of ASR and the net radiation fluxes and nearly 90% of the variance of OLR over land. Because one term can express so much of the variance, principal component analysis is very useful to describe these seasonal cycles. The annual cycles of ASR are about 100 W m−2 over land and ocean, but the amplitudes of OLR are about 27 W m−2 over land and 15 W m−2 over ocean. The magnitude of OLR and its time lag relative to that of ASR are important descriptors of the climate system and are computed for the first principal components. OLR lags ASR by about 26 days over land and 42 days over ocean. The principal components are useful for comparing the observed radiation budget with that computed by a model.

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David R. Doelling
,
Conor O. Haney
,
Benjamin R. Scarino
,
Arun Gopalan
, and
Rajendra Bhatt

Abstract

The Clouds and the Earth’s Radiant Energy System (CERES) project relies on geostationary imager–derived TOA broadband fluxes and cloud properties to account for the regional diurnal fluctuations between the Terra and Aqua CERES and MODIS measurements. The CERES project employs a ray-matching calibration algorithm in order to transfer the Aqua MODIS calibration to the geostationary (GEO) imagers, thereby allowing the derivation of consistent fluxes and cloud retrievals across the 16 GEO imagers utilized in the CERES record. The CERES Edition 4 processing scheme grants the opportunity to recalibrate the GEO record using an improved GEO/MODIS all-sky ocean ray-matching algorithm. Using a graduated angle matching method, which is most restrictive for anisotropic clear-sky ocean radiances and least restrictive for isotropic bright cloud radiances, reduces the bidirectional bias while preserving the dynamic range. Furthermore, SCIAMACHY hyperspectral radiances are used to account for both the solar incoming and Earth-reflected spectra in order to correct spectral band differences. As a result, the difference between the linear regression offset and the maintained GEO space count was reduced, and the calibration slopes computed from the linear fit and the regression through the space count agreed to within 0.4%. A deep convective cloud (DCC) ray-matching algorithm is also presented. The all-sky ocean and DCC ray-matching timeline gains are within 0.7% of one another. Because DCC are isotropic and the brightest, Earth targets with near-uniform visible spectra, the temporal standard error of GEO imager gains, are reduced by up to 60% from that of all-sky ocean targets.

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Norman G. Loeb
,
Seiji Kato
,
Konstantin Loukachine
,
Natividad Manalo-Smith
, and
David R. Doelling

Abstract

Errors in top-of-atmosphere (TOA) radiative fluxes from the Clouds and the Earth’s Radiant Energy System (CERES) instrument due to uncertainties in radiance-to-flux conversion from CERES Terra angular distribution models (ADMs) are evaluated through a series of consistency tests. These tests show that the overall bias in regional monthly mean shortwave (SW) TOA flux is less than 0.2 W m−2 and the regional RMS error ranges from 0.70 to 1.4 W m−2. In contrast, SW TOA fluxes inferred using theoretical ADMs that assume clouds are plane parallel are overestimated by 3–4 W m−2 and exhibit a strong latitudinal dependence. In the longwave (LW), the bias error ranges from 0.2 to 0.4 W m−2 and regional RMS errors remain smaller than 0.7 W m−2. Global mean albedos derived from ADMs developed during the Earth Radiation Budget Experiment (ERBE) and applied to CERES measurements show a systematic increase with viewing zenith angle of 4%–8%, while albedos from the CERES Terra ADMs show a smaller increase of 1%–2%. The LW fluxes from the ERBE ADMs show a systematic decrease with viewing zenith angle of 2%–2.4%, whereas fluxes from the CERES Terra ADMs remain within 0.7%–0.8% at all angles. Based on several months of multiangle CERES along-track data, the SW TOA flux consistency between nadir- and oblique-viewing zenith angles is generally 5% (<17 W m−2) over land and ocean and 9% (26 W m−2) in polar regions, and LW TOA flux consistency is approximate 3% (7 W m−2) over all surfaces. Based on these results and a theoretically derived conversion between TOA flux consistency and TOA flux error, the best estimate of the error in CERES TOA flux due to the radiance-to-flux conversion is 3% (10 W m−2) in the SW and 1.8% (3–5 W m−2) in the LW. Monthly mean TOA fluxes based on ERBE ADMs are larger than monthly mean TOA fluxes based on CERES Terra ADMs by 1.8 and 1.3 W m−2 in the SW and LW, respectively.

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Patrick Minnis
,
David R. Doelling
,
Louis Nguyen
,
Walter F. Miller
, and
Venkatesan Chakrapani

Abstract

Several recent research satellites carry self-calibrating multispectral imagers that can be used for calibrating operational imagers lacking complete self-calibrating capabilities. In particular, the visible (VIS, 0.65 μm) channels on operational meteorological satellites are generally calibrated before launch, but require vicarious calibration techniques to monitor the gains and offsets once they are in orbit. To ensure that the self-calibrating instruments are performing as expected, this paper examines the consistencies between the VIS channel (channel 1) reflectances of the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra and Aqua satellites and the version 5a and 6 reflectances of the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission using a variety of techniques. These include comparisons of Terra and Aqua VIS radiances with coincident broadband shortwave radiances from the well-calibrated Clouds and the Earth’s Radiant Energy System (CERES), time series of deep convective cloud (DCC) albedos, and ray-matching intercalibrations between each of the three satellites. Time series of matched Terra and VIRS data, Aqua and VIRS data, and DCC reflected fluxes reveal that an older version (version 5a, ending in early 2004) of the VIRS calibration produced a highly stable record, while the latest version (version 6) appears to overestimate the sensor gain change by ∼1% yr−1 as the result of a manually induced gain adjustment. Comparisons with the CERES shortwave radiances unearthed a sudden change in the Terra MODIS calibration that caused a 1.17% decrease in the gain on 19 November 2003 that can be easily reversed. After correction for these manual adjustments, the trends in the VIRS and Terra channels are no greater than 0.1% yr−1. Although the results were more ambiguous, no statistically significant trends were found in the Aqua MODIS channel 1 gain. The Aqua radiances are 1% greater, on average, than their Terra counterparts, and after normalization are 4.6% greater than VIRS radiances, in agreement with theoretical calculations. The discrepancy between the two MODIS instruments should be taken into account to ensure consistency between parameters derived from them. With the adjustments, any of the three instruments can serve as references for calibrating other satellites. Monitoring of the calibrations continues in near–real time and the results are available via the World Wide Web.

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Patrick Minnis
,
Louis Nguyen
,
David R. Doelling
,
David F. Young
,
Walter F. Miller
, and
David P. Kratz

Abstract

Operational meteorological satellites generally lack reliable onboard calibration systems for solar-imaging channels. Current methods for calibrating these channels and for normalizing similar channels on contemporaneous satellite imagers typically rely on a poorly calibrated reference source. To establish a more reliable reference instrument for calibration normalization, this paper examines the use of research satellite imagers that maintain their solar-channel calibrations by using onboard diffuser systems that rely on the sun as an absolute reference. The Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and the second Along-Track Scanning Radiometer (ATSR-2) on the second European Remote Sensing Satellite (ERS-2) are correlated with matched data from the eighth Geostationary Operational Environmental Satellite (GOES-8), the fifth Geostationary Meteorological satellite (GMS-5), and with each other to examine trends in the solar channels. VIRS data are also correlated with the Terra satellite's Moderate Resolution Imaging Spectroradiometer (MODIS) provisional data as a preliminary assessment of their relative calibrations. As an additional check on their long-term stability, the VIRS data are compared to the relevant corresponding broadband shortwave radiances of the Clouds and the Earth's Radiant Energy System (CERES) scanners on TRMM. No statistically significant trend in the calibration of the VIRS 0.65- and 1.64-μm channels could be detected from the comparisons with CERES data taken during 1998 and 2000. The VIRS-to-GOES-8 correlations revealed an annual degradation rate for the GOES-8 visible (0.67 μm) channel of ∼7.5% and an initial drop of 16% in the gain from the prelaunch value. The slopes in the GOES-8 visible-channel gain trend lines derived from VIRS data taken after January 1998 and ATSR-2 data taken between October 1995 and December 1999 differed by only 1%–2% indicating that both reference instruments are highly stable. The mean difference of 3%–4.8% between the VIRS–GOES-8 and ATSR-2–GOES-8 gains is attributed to spectral differences between ATSR-2 and VIRS and to possible biases in the ATSR-2 channel-2 calibration. A degradation rate of 1.3% per year found for the GMS-5 visible channel was confirmed by comparisons with earlier calibrations. The MODIS and VIRS calibrations agreed to within −1% to 3%. Some of the differences between VIRS and the provisional MODIS radiances can be explained by spectral differences between the two instruments. The MODIS measures greater reflectance than VIRS for bright scenes. Although both VIRS and ATSR-2 provide temporally stable calibrations, it is recommended that, at least until MODIS calibrations are finalized, VIRS should be used as a reference source for normalizing operational meteorological satellite imagers because of its broader visible filter.

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Patrick Minnis
,
Louis Nguyen
,
David R. Doelling
,
David F. Young
,
Walter F. Miller
, and
David P. Kratz

Abstract

To establish a more reliable reference instrument for calibration normalization, this paper examines the differences between the various thermal infrared imager channels on a set of research and operational satellites. Mean brightness temperatures from the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and the second Along-Track Scanning Radiometer (ATSR-2) on the second European Remote Sensing Satellite (ERS-2) are correlated with matched data from the eighth Geostationary Operational Environmental Satellite (GOES-8), the fifth Geostationary Meteorological Satellite (GMS-5), and with each other. VIRS data are also correlated with the Terra satellite's Moderate Resolution Imaging Spectroradiometer (MODIS) provisional data as a preliminary assessment of their relative calibrations. As an additional check on their long-term stability, the VIRS data are compared to the broadband longwave radiances of the Clouds and the Earth's Radiant Energy System (CERES) scanners on TRMM. No statistically significant trend in the calibration of any of the three (3.7, 10.8, and 12.0 μm) VIRS thermal channels could be detected from the comparisons with CERES data taken during 1998 and 2000 indicating that the VIRS channels can serve as a reliable reference for intercalibrating satellite imagers. However, a small day–night difference in the VIRS thermal channels detected at very low temperatures should be taken into account. In general, most of the channels agreed to within less than ±0.7 K over a temperature range between 200 and 300 K. Some of the smaller differences can be explained by spectral differences in the channel response functions. A few larger differences were found at 200 K for some of the channels suggesting some basic calibration differences for lower temperatures. A nearly 3-K bias in the ATSR-2 11-μm channel relative to VIRS and GOES-8 was found at the cold end of the temperature range. The intercalibrations described here are being continued on a routine basis.

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David A. Rutan
,
Seiji Kato
,
David R. Doelling
,
Fred G. Rose
,
Le Trang Nguyen
,
Thomas E. Caldwell
, and
Norman G. Loeb

Abstract

The Clouds and the Earth’s Radiant Energy System Synoptic (SYN1deg), edition 3, product provides climate-quality global 3-hourly 1° × 1°gridded top of atmosphere, in-atmosphere, and surface radiant fluxes. The in-atmosphere surface fluxes are computed hourly using a radiative transfer code based upon inputs from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), 3-hourly geostationary (GEO) data, and meteorological assimilation data from the Goddard Earth Observing System. The GEO visible and infrared imager calibration is tied to MODIS to ensure uniform MODIS-like cloud properties across all satellite cloud datasets. Computed surface radiant fluxes are compared to surface observations at 85 globally distributed land (37) and ocean buoy (48) sites as well as several other publicly available global surface radiant flux data products. Computed monthly mean downward fluxes from SYN1deg have a bias (standard deviation) of 3.0 W m−2 (5.7%) for shortwave and −4.0 W m−2 (2.9%) for longwave compared to surface observations. The standard deviation between surface downward shortwave flux calculations and observations at the 3-hourly time scale is reduced when the diurnal cycle of cloud changes is explicitly accounted for. The improvement is smaller for surface downward longwave flux owing to an additional sensitivity to boundary layer temperature/humidity, which has a weaker diurnal cycle compared to clouds.

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David R. Doelling
,
Norman G. Loeb
,
Dennis F. Keyes
,
Michele L. Nordeen
,
Daniel Morstad
,
Cathy Nguyen
,
Bruce A. Wielicki
,
David F. Young
, and
Moguo Sun

Abstract

The Clouds and the Earth’s Radiant Energy System (CERES) instruments on board the Terra and Aqua spacecraft continue to provide an unprecedented global climate record of the earth’s top-of-atmosphere (TOA) energy budget since March 2000. A critical step in determining accurate daily averaged flux involves estimating the flux between CERES Terra or Aqua overpass times. CERES employs the CERES-only (CO) and the CERES geostationary (CG) temporal interpolation methods. The CO method assumes that the cloud properties at the time of the CERES observation remain constant and that it only accounts for changes in albedo with solar zenith angle and diurnal land heating, by assuming a shape for unresolved changes in the diurnal cycle. The CG method enhances the CERES data by explicitly accounting for changes in cloud and radiation between CERES observation times using 3-hourly imager data from five geostationary (GEO) satellites. To maintain calibration traceability, GEO radiances are calibrated against Moderate Resolution Imaging Spectroradiometer (MODIS) and the derived GEO fluxes are normalized to the CERES measurements. While the regional (1° latitude × 1° longitude) monthly-mean difference between the CG and CO methods can exceed 25 W m−2 over marine stratus and land convection, these regional biases nearly cancel in the global mean. The regional monthly CG shortwave (SW) and longwave (LW) flux uncertainty is reduced by 20%, whereas the daily uncertainty is reduced by 50% and 20%, respectively, over the CO method, based on comparisons with 15-min Geostationary Earth Radiation Budget (GERB) data.

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Norman G. Loeb
,
Fred G. Rose
,
Seiji Kato
,
David A. Rutan
,
Wenying Su
,
Hailan Wang
,
David R. Doelling
,
William L. Smith
, and
Andrew Gettelman

Abstract

A new method of determining clear-sky radiative fluxes from satellite observations for climate model evaluation is presented. The method consists of applying adjustment factors to existing satellite clear-sky broadband radiative fluxes that make the observed and simulated clear-sky flux definitions more consistent. The adjustment factors are determined from the difference between observation-based radiative transfer model calculations of monthly mean clear-sky fluxes obtained by ignoring clouds in the atmospheric column and by weighting hourly mean clear-sky fluxes with imager-based clear-area fractions. The global mean longwave (LW) adjustment factor is −2.2 W m−2 at the top of the atmosphere and 2.7 W m−2 at the surface. The LW adjustment factors are pronounced at high latitudes during winter and in regions with high upper-tropospheric humidity and cirrus cloud cover, such as over the west tropical Pacific, and the South Pacific and intertropical convergence zones. In the shortwave (SW), global mean adjustment is 0.5 W m−2 at TOA and −1.9 W m−2 at the surface. It is most pronounced over sea ice off of Antarctica and over heavy aerosol regions, such as eastern China. However, interannual variations in the regional SW and LW adjustment factors are small compared to those in cloud radiative effect. After applying the LW adjustment factors, differences in zonal mean cloud radiative effect between observations and climate models decrease markedly between 60°S and 60°N and poleward of 65°N. The largest regional improvements occur over the west tropical Pacific and Indian Oceans. In contrast, the impact of the SW adjustment factors is much smaller.

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