The ScaRaB–Resurs Earth Radiation Budget Dataset and First Results

Duvel, Jean-Philippe; Viollier, M.; Raberanto, Patrick; Kandel, Robert S.; Haeffelin, Martial; Pakhomov, L. A.; Golovko, Vladimir; Mueller, Johannes; Stuhlmann, R.

doi:10.1175/1520-0477(2001)082<1397:tsrerb>2.3.co;2

Cited by 39 publications

(18 citation statements)

References 38 publications

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“…The mean global OSR has a very small seasonal variability of about 15 Wm −2 , i.e. between 95 and 110 Wm −2 , with a minimum in late summer -early autumn, in excellent agreement with satellite measurements (Duvel et al, 2001). The mean hemispherical planetary albedo does not show great seasonality; it varies between 27.5% (minimum value in October) and 29.9% (maximum value in June) for Northern Hemisphere, and between 26.6% (minimum in June) and 31.3% (maximum in December) for Southern Hemisphere.…”

Section: Time Seriessupporting

confidence: 71%

Long-term global distribution of earth's shortwave radiation budget at the top of atmosphere

et al. 2004

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Abstract. The mean monthly shortwave (SW) radiation budget at the top of atmosphere (TOA) was computed on 2.5 • longitude-latitude resolution for the 14-year period from 1984 to 1997, using a radiative transfer model with long-term climatological data from the International Satellite Cloud Climatology Project (ISCCP-D2) supplemented by data from the National Centers for Environmental Prediction -National Center for Atmospheric Research (NCEP-NCAR) Global Reanalysis project, and other global data bases such as TIROS Operational Vertical Sounder (TOVS) and Global Aerosol Data Set (GADS). The model radiative fluxes at TOA were validated against Earth Radiation Budget Experiment (ERBE) S4 scanner satellite data (1985)(1986)(1987)(1988)(1989). The model is able to predict the seasonal and geographical variation of SW TOA fluxes. On a mean annual and global basis, the model is in very good agreement with ERBE, overestimating the outgoing SW radiation at TOA (OSR) by 0.93 Wm −2 (or by 0.92%), within the ERBE uncertainties. At pixel level, the OSR differences between model and ERBE are mostly within ±10 Wm −2 , with ±5 Wm −2 over extended regions, while there exist some geographic areas with differences of up to 40 Wm −2 , associated with uncertainties in cloud properties and surface albedo. The 14-year average model results give a planetary albedo equal to 29.6% and a TOA OSR flux of 101.2 Wm −2 . A significant linearly decreasing trend in OSR and planetary albedo was found, equal to 2.3 Wm −2 and 0.6% (in absolute values), respectively, over the 14-year period (from January 1984 to December 1997)

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Section: Time Seriessupporting

confidence: 71%

Long-term global distribution of earth's shortwave radiation budget at the top of atmosphere

et al. 2004

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“…Similarly, the annual mean TOA longwave irradiance is 239 W m 22 and the difference between the maximum and minimum values is 0.3 W m 22 , which is only 0.1% of the mean value. Somewhat larger variability of TOA reflected shortwave, longwave, and net irradiance is also reported by Duvel et al (2001), who used Earth Radiation Budget Experiment (ERBE), Scanner for Radiation Budget (ScaRaB)-Meteor Satellite, and ScaRaB data, but it is still small compared with the mean values. In addition, according to Loeb et al (2007b), shortwave variability from the International Satellite Cloud Climatology Project (ISCCP; Schiffer and Rossow 1983) is consistent to 40% with that from CERES.…”

Section: Introductionmentioning

confidence: 78%

Interannual Variability of the Global Radiation Budget

Kato

2009

Journal of Climate

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Interannual variability of the global radiation budget, regions that contribute to its variability, and what limits albedo variability are investigated using Clouds and the Earth's Radiant Energy System (CERES) data taken from March 2000 through February 2004. Area-weighted mean top-of-atmosphere (TOA) reflected shortwave, longwave, and net irradiance standard deviations computed from monthly anomalies over a 18 3 18 region are 9.6, 7.6, and 7.6 W m 22 , respectively. When standard deviations are computed from global monthly anomalies, they drop to 0.5, 0.4, and 0.4 W m 22 , respectively. Clouds are mostly responsible for the variation. Regions with a large standard deviation of TOA shortwave and longwave irradiance at TOA are the tropical western and central Pacific, which is caused by shifting from La Niñ a to El Niñ o during this period. However, a larger standard deviation of 300-1000-hPa thickness anomalies occurs in the polar region instead of the tropics. The correlation coefficient between atmospheric net irradiance anomalies and 300-1000-hPa thickness anomalies is negative. These indicate that temperature anomalies in the atmosphere are mostly a result of anomalies in longwave and dynamical processes that transport energy poleward, instead of albedo anomalies by clouds directly affecting temperature anomalies in the atmosphere. With simple zonal-mean thermodynamic energy equations it is demonstrated that temperature anomalies decay exponentially with time by longwave emission and by dynamical processes. As a result, the mean meridional temperature gradient is maintained. Therefore, mean meridional circulations are not greatly altered by albedo anomalies on an annual time scale, which in turn provides small interannual variability of the global mean albedo.

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“…Continuous measurements began in 2000 with the Clouds and Earth's Radiant Energy System (CERES) radiometers (Wielicki et al 1995;Loeb et al 2009) on two satellites from 2002 and continues today. In addition, the FrenchSoviet-German Scanner for Radiation Budget experiment (ScaRaB; Duvel et al 2001) provided intermittent coverage for several months in 1995 and 1999 and has provided data since 2012 from the near-equatorial satellite Megha-Tropiques. Regionally limited but high temporal resolution data have been obtained by the Geostationary Earth Radiation Budget instrument (GERB; Harries et al 2005) on the geostationary Meteosat platforms since 1998.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Radiative Energy Flows in Observational Datasets and Climate Modeling

Raschke

Kinne

Rossow

et al. 2016

Journal of Applied Meteorology and Climatology

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This study examines radiative flux distributions and local spread of values from three major observational datasets (CERES, ISCCP, and SRB) and compares them with results from climate modeling (CMIP3). Examinations of the spread and differences also differentiate among contributions from cloudy and clear-sky conditions. The spread among observational datasets is in large part caused by noncloud ancillary data. Average differences of at least 10 W m 22 each for clear-sky downward solar, upward solar, and upward infrared fluxes at the surface demonstrate via spatial difference patterns major differences in assumptions for atmospheric aerosol, solar surface albedo and surface temperature, and/or emittance in observational datasets. At the top of the atmosphere (TOA), observational datasets are less influenced by the ancillary data errors than at the surface.

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The ScaRaB–Resurs Earth Radiation Budget Dataset and First Results

Cited by 39 publications

References 38 publications

Long-term global distribution of earth's shortwave radiation budget at the top of atmosphere

Long-term global distribution of earth's shortwave radiation budget at the top of atmosphere

Interannual Variability of the Global Radiation Budget

Comparison of Radiative Energy Flows in Observational Datasets and Climate Modeling

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