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

Loeb, Norman G.; Kato, Seiji; Loukachine, K.; Manalo‐Smith, Natividad

doi:10.1175/jtech1712.1

Cited by 285 publications

(261 citation statements)

References 34 publications

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“…Hereafter, these products are denoted as cloud products derived from the CERES cloud algorithm. The TOA shortwave and longwave irradiances are derived from CERES radiance measurements using angular distribution models described by Loeb et al [2005] and Kato and Loeb [2005]. All irradiances and cloud properties are taken from the Single Scanner Footprint (SSF) Eddition2B Rev1 product for Terra and Eddition1B product for Aqua, which are available from the NASA Langley Atmospheric Science Data Center.…”

Section: Introductionmentioning

confidence: 99%

Seasonal and interannual variations of top‐of‐atmosphere irradiance and cloud cover over polar regions derived from the CERES data set

Kato¹,

Loeb²,

Minnis³

et al. 2006

Geophysical Research Letters

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[1] The daytime cloud fraction derived by the Clouds and the Earth's Radiant Energy System (CERES) cloud algorithm using Moderate Resolution Imaging Spectroradiometer (MODIS) radiances over the Arctic from March 2000 through February 2004 increases at a rate of 0.047 per decade. The trend is significant at an 80% confidence level. The corresponding top-of-atmosphere (TOA) shortwave irradiances derived from CERES radiance measurements show less significant trend during this period. These results suggest that the influence of reduced Arctic sea ice cover on TOA reflected shortwave radiation is reduced by the presence of clouds and possibly compensated by the increase in cloud cover. The cloud fraction and TOA reflected shortwave irradiance over the Antarctic show no significant trend during the same period.

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Section: Introductionmentioning

confidence: 99%

Seasonal and interannual variations of top‐of‐atmosphere irradiance and cloud cover over polar regions derived from the CERES data set

Kato¹,

Loeb²,

Minnis³

et al. 2006

Geophysical Research Letters

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“…Two versions of the CERES data analysis (8,9) are used in this study. In the first version, CERES SRBAVG (SRBAVG1-Terra-FM1-MODISEdition2D-GEO) (8), the TOA fluxes are estimated from unfiltered radiances using new angular distribution models (18,19). In the second version, called CERES EBAF (9), the global monthly mean TOA fluxes of the CERES SRBAVG are adjusted such that they are consistent with the observed, global heat storage of the Earth-atmosphere system.…”

Section: Methodsmentioning

confidence: 99%

Assessment of radiative feedback in climate models using satellite observations of annual flux variation

Tsushima

2013

Proc. Natl. Acad. Sci. U.S.A.

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In the climate system, two types of radiative feedback are in operation. The feedback of the first kind involves the radiative damping of the vertically uniform temperature perturbation of the troposphere and Earth's surface that approximately follows the StefanBoltzmann law of blackbody radiation. The second kind involves the change in the vertical lapse rate of temperature, water vapor, and clouds in the troposphere and albedo of the Earth's surface. Using satellite observations of the annual variation of the outgoing flux of longwave radiation and that of reflected solar radiation at the top of the atmosphere, this study estimates the so-called "gain factor," which characterizes the strength of radiative feedback of the second kind that operates on the annually varying, global-scale perturbation of temperature at the Earth's surface. The gain factor is computed not only for all sky but also for clear sky. The gain factor of socalled "cloud radiative forcing" is then computed as the difference between the two. The gain factors thus obtained are compared with those obtained from 35 models that were used for the fourth and fifth Intergovernmental Panel on Climate Change assessment. Here, we show that the gain factors obtained from satellite observations of cloud radiative forcing are effective for identifying systematic biases of the feedback processes that control the sensitivity of simulated climate, providing useful information for validating and improving a climate model.O ne of the most challenging tasks of climate science is to determine climate sensitivity. It is often defined as the equilibrium response of the global mean surface temperature to the doubling of atmospheric CO 2 . Unfortunately, currently available models have sensitivities that vary across a wide range. According to the report of the fourth Intergovernmental Panel on Climate Change (IPCC) assessment (1), about two-thirds of the current climate models have sensitivities that range between 2°C and 4.5°C. Although this range is itself large, the sensitivities of one-third of the models lie outside of this range. The need to reduce this sizable uncertainty is one of the important reasons it is urgent to understand and reliably quantify the mechanisms that determine climate sensitivity.Climate sensitivity is inversely proportional to the strength of the radiative feedback that operates on the global-scale perturbation of surface temperature. Here, we describe our attempt to estimate the strength of the radiative feedback that operates on the global-scale perturbation of surface temperature in many current climate models and compare the results with those obtained from satellite observations. The geographical pattern of the perturbation chosen for the present analysis, however, is the annual variation, rather than global warming.The annual variation of the global mean surface temperature is attributable mainly to the difference in the amplitude of the seasonal variation of the hemispheric mean temperature that is out of phase between the two he...

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“…The time period considered in this study is from March 2000 to May 2007. Further details are found in Loeb et al (2005Loeb et al ( , 2007. The TOA SW fluxes have a small positive bias of 0.2 W m −2 for regional monthly averages and root mean square (RMS) errors between 0.7 and 1.4 W m −2 .…”

Section: Satellite-derived Climatology Of Toa Fluxesmentioning

confidence: 98%

Comparison of satellite‐derived TOA shortwave clear‐sky fluxes to estimates from GCM simulations constrained by satellite observations of land surface characteristics

Anantharaj

Nair

Lawrence

et al. 2010

Intl Journal of Climatology

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Clear-sky, upwelling shortwave flux at the top of the atmosphere S ↑ TOA , simulated using the atmospheric and land model components of the Community Climate System Model 3 (CCSM3), is compared to corresponding observational estimates from the Clouds and Earth's Radiant Energy System (CERES) sensor. Improvements resulting from the use of land surface albedo derived from Moderate Resolution Imaging Spectroradiometer (MODIS) to constrain the simulations are also examined. Compared to CERES observations, CCSM3 overestimates global, annual averaged S ↑ TOA over both land and oceans. However, regionally, CCSM3 overestimates S ↑ TOA over some land and ocean areas while underestimating it over other sites. CCSM3 underestimates S ↑ TOA over the Saharan and Arabian Deserts and substantial differences exist between CERES observations and CCSM3 over agricultural areas. Over selected sites, after using groundbased observations to remove systematic biases that exist in CCSM computation of S ↑ TOA , it is found that use of MODIS albedo improves the simulation of S ↑ TOA . Inability of coarse resolution CCSM3 simulation to resolve spatial heterogeneity of snowfall over high altitude sites such as the Tibetan Plateau causes overestimation of S ↑ TOA in these areas. Discrepancies also exist in the simulation of S ↑ TOA over ocean areas as CCSM3 does not account for the effect of wind speed on ocean surface albedo. This study shows that the radiative energy budget at the TOA is improved through the use of MODIS albedo in Global Climate Models.

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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

Cited by 285 publications

References 34 publications

Seasonal and interannual variations of top‐of‐atmosphere irradiance and cloud cover over polar regions derived from the CERES data set

Seasonal and interannual variations of top‐of‐atmosphere irradiance and cloud cover over polar regions derived from the CERES data set

Assessment of radiative feedback in climate models using satellite observations of annual flux variation

Comparison of satellite‐derived TOA shortwave clear‐sky fluxes to estimates from GCM simulations constrained by satellite observations of land surface characteristics

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