NPP clouds and the Earth's Radiant Energy System (CERES) predicted sensor performance calibration and preliminary data product performance

The Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) top-of-atmosphere (TOA), Edition 4.0 (Ed4.0), data product is described. EBAF Ed4.0 is an update to EBAF Ed2.8, incorporating all of the Ed4.0 suite of CERES data product algorithm improvements and consistent input datasets throughout the record. A one-time adjustment to shortwave (SW) and longwave (LW) TOA fluxes is made to ensure that global mean net TOA flux for July 2005–June 2015 is consistent with the in situ value of 0.71 W m−2. While global mean all-sky TOA flux differences between Ed4.0 and Ed2.8 are within 0.5 W m−2, appreciable SW regional differences occur over marine stratocumulus and snow/sea ice regions. Marked regional differences in SW clear-sky TOA flux occur in polar regions and dust areas over ocean. Clear-sky LW TOA fluxes in EBAF Ed4.0 exceed Ed2.8 in regions of persistent high cloud cover. Owing to substantial differences in global mean clear-sky TOA fluxes, the net cloud radiative effect in EBAF Ed4.0 is −18 W m−2 compared to −21 W m−2 in EBAF Ed2.8. The overall uncertainty in 1° × 1° latitude–longitude regional monthly all-sky TOA flux is estimated to be 3 W m−2 [one standard deviation (1 σ)] for the Terra-only period and 2.5 W m−2 for the Terra– Aqua period both for SW and LW fluxes. The SW clear-sky regional monthly flux uncertainty is estimated to be 6 W m−2 for the Terra-only period and 5 W m−2 for the Terra– Aqua period. The LW clear-sky regional monthly flux uncertainty is 5 W m−2 for Terra only and 4.5 W m−2 for Terra– Aqua.

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Sensor performance of Clouds and the Earth's Radiant Energy System (CERES) instruments aboard EOS Terra and Aqua spacecraft based on post-launch calibration studies

10.1117/12.828487 ◽

2009 ◽

Cited By ~ 1

Author(s):

Susan Thomas ◽

K. J. Priestley ◽

P. C. Hess ◽

R. S. Wilson ◽

M. A. Avery ◽

...

Keyword(s):

Radiant Energy ◽

Energy System ◽

Sensor Performance

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Surface Irradiances of Edition 4.0 Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Data Product

Journal of Climate ◽

10.1175/jcli-d-17-0523.1 ◽

2018 ◽

Vol 31 (11) ◽

pp. 4501-4527 ◽

Cited By ~ 77

Author(s):

Seiji Kato ◽

Fred G. Rose ◽

David A. Rutan ◽

Tyler J. Thorsen ◽

Norman G. Loeb ◽

...

Keyword(s):

Lagrange Multiplier ◽

Spatial Scales ◽

Radiant Energy ◽

Energy System ◽

Specific Humidity ◽

Adjustment Process ◽

Polar Regions ◽

Atmospheric Infrared Sounder ◽

Data Product ◽

Surface Data

Abstract The algorithm to produce the Clouds and the Earth’s Radiant Energy System (CERES) Edition 4.0 (Ed4) Energy Balanced and Filled (EBAF)-surface data product is explained. The algorithm forces computed top-of-atmosphere (TOA) irradiances to match with Ed4 EBAF-TOA irradiances by adjusting surface, cloud, and atmospheric properties. Surface irradiances are subsequently adjusted using radiative kernels. The adjustment process is composed of two parts: bias correction and Lagrange multiplier. The bias in temperature and specific humidity between 200 and 500 hPa used for the irradiance computation is corrected based on observations by Atmospheric Infrared Sounder (AIRS). Similarly, the bias in the cloud fraction is corrected based on observations by Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat. Remaining errors in surface, cloud, and atmospheric properties are corrected in the Lagrange multiplier process. Ed4 global annual mean (January 2005 through December 2014) surface net shortwave (SW) and longwave (LW) irradiances increase by 1.3 W m−2 and decrease by 0.2 W m−2, respectively, compared to EBAF Edition 2.8 (Ed2.8) counterparts (the previous version), resulting in an increase in net SW + LW surface irradiance of 1.1 W m−2. The uncertainty in surface irradiances over ocean, land, and polar regions at various spatial scales are estimated. The uncertainties in all-sky global annual mean upward and downward shortwave irradiance are 3 and 4 W m−2, respectively, and the uncertainties in upward and downward longwave irradiance are 3 and 6 W m−2, respectively. With an assumption of all errors being independent, the uncertainty in the global annual mean surface LW + SW net irradiance is 8 W m−2.

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CERES Energy Balanced and Filled (EBAF) from Afternoon-Only Satellite Orbits

Remote Sensing ◽

10.3390/rs12081280 ◽

2020 ◽

Vol 12 (8) ◽

pp. 1280 ◽

Cited By ~ 1

Author(s):

Norman G. Loeb ◽

David R. Doelling

Keyword(s):

Time Series ◽

Radiant Energy ◽

Energy System ◽

Satellite Orbits ◽

Data Product ◽

The Difference ◽

The Stability ◽

Terra Satellite ◽

Observation Times ◽

Diurnal Correction

The Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) data product uses a diurnal correction methodology to produce a shortwave (SW) top-of-atmosphere (TOA) radiative flux time series that accounts for diurnal cycle changes between CERES observation times while ensuring that the stability of the EBAF record is tied as closely as possible to CERES instrument calibration stability. The current EBAF Ed4.1 data product combines observations from Terra and Aqua after July 2002. However, the Terra satellite will start to drift in Mean Local Time (MLT) in early 2021, and Aqua’s MLT will start to drift in 2022. To ensure the EBAF record remains temporally stable, we explore the feasibility of using only CERES instruments from afternoon satellite orbits with a tight 1330 MLT after July 2002. We test this approach by directly comparing SW TOA fluxes generated after applying diurnal corrections to Aqua-only and to Terra + Aqua for 07/2002–06/2019. We find that global climatological mean SW TOA fluxes for these two cases are within 0.01 Wm−2 and the trend of the difference is < is 0.03 Wm−2 per decade.

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Development and assessment of broadband surface albedo from Clouds and the Earth's Radiant Energy System Clouds and Radiation Swath data product

Journal of Geophysical Research Atmospheres ◽

10.1029/2008jd010669 ◽

2009 ◽

Vol 114 (D8) ◽

Cited By ~ 59

Author(s):

David Rutan ◽

Fred Rose ◽

Miguel Roman ◽

Natividad Manalo‐Smith ◽

Crystal Schaaf ◽

...

Keyword(s):

Surface Albedo ◽

Radiant Energy ◽

Energy System ◽

Data Product

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Evaluation of net shortwave radiation over China with a regional climate model

Climate Research ◽

10.3354/cr01598 ◽

2020 ◽

Vol 80 (2) ◽

pp. 147-163

Author(s):

X Liu ◽

Y Kang ◽

Q Liu ◽

Z Guo ◽

Y Chen ◽

...

Keyword(s):

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Radiant Energy ◽

Energy System ◽

Radiation Budget ◽

Shortwave Radiation ◽

Monsoon Region ◽

Clear Sky ◽

Sky Conditions

The regional climate model RegCM version 4.6, developed by the European Centre for Medium-Range Weather Forecasts Reanalysis, was used to simulate the radiation budget over China. Clouds and the Earth’s Radiant Energy System (CERES) satellite data were utilized to evaluate the simulation results based on 4 radiative components: net shortwave (NSW) radiation at the surface of the earth and top of the atmosphere (TOA) under all-sky and clear-sky conditions. The performance of the model for low-value areas of NSW was superior to that for high-value areas. NSW at the surface and TOA under all-sky conditions was significantly underestimated; the spatial distribution of the bias was negative in the north and positive in the south, bounded by 25°N for the annual and seasonal averaged difference maps. Compared with the all-sky condition, the simulation effect under clear-sky conditions was significantly better, which indicates that the cloud fraction is the key factor affecting the accuracy of the simulation. In particular, the bias of the TOA NSW under the clear-sky condition was <±10 W m-2 in the eastern areas. The performance of the model was better over the eastern monsoon region in winter and autumn for surface NSW under clear-sky conditions, which may be related to different levels of air pollution during each season. Among the 3 areas, the regional average biases overall were largest (negative) over the Qinghai-Tibet alpine region and smallest over the eastern monsoon region.

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