scholarly journals Coloration determination of spectral darkening occurring on a broadband Earth observing radiometer: application to Clouds and the Earth's Radiant Energy System (CERES)

Author(s):  
Grant Matthews ◽  
Kory Priestley ◽  
Norman G. Loeb ◽  
Konstantin Loukachine ◽  
Susan Thomas ◽  
...  
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2001 ◽  
Vol 40 (4) ◽  
pp. 822-835 ◽  
Author(s):  
Norman G. Loeb ◽  
Kory J. Priestley ◽  
David P. Kratz ◽  
Erika B. Geier ◽  
Richard N. Green ◽  
...  
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2006 ◽  
Author(s):  
Grant Matthews ◽  
Kory Priestley ◽  
Norman G. Loeb ◽  
Konstantin Loukachine ◽  
Susan Thomas ◽  
...  
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2020 ◽  
Vol 80 (2) ◽  
pp. 147-163
Author(s):  
X Liu ◽  
Y Kang ◽  
Q Liu ◽  
Z Guo ◽  
Y Chen ◽  
...  

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.


2018 ◽  
Vol 3 (3) ◽  
pp. 1029-1039 ◽  
Author(s):  
Luis O Tedeschi

Abstract Interrelationships between retained energy (RE) and retained protein (RP) that are essential in determining the efficiency of use of feeds and the assessment of energy and protein requirements of growing cattle were analyzed. Two concerns were identified. The first concern was the conundrum of a satisfactory correlation between observed and predicted RE (r = 0.93) or between observed and predicted RP when using predicted RE to estimate RP (r = 0.939), but a much lower correlation between observed and predicted RP when using observed RE to estimate RP (r = 0.679). The higher correlation when using predicted vs. observed RE is a concern because it indicates an interdependency between predicted RP and predicted RE that is needed to predict RP with a higher precision. These internal offsetting errors create an apparent overall adequacy of nutrition modeling that is elusive, thus potentially destabilizing the predictability of nutrition models when submodels are changed independently. In part, the unsatisfactory prediction of RP from observed RE might be related to the fact that body fat has a caloric value that is 1.65 times greater than body protein and the body deposition of fat increases exponentially as an animal matures, whereas body deposition of protein tends to plateau. Thus, body fat is more influential than body protein in determining RE, and inaccuracies in measuring body protein will be reflected in the RP comparison but suppressed in the RE calculation. The second concern is related to the disconnection when predicting partial efficiency of use of metabolizable energy for growth (kG) using the proportion of RE deposited as protein—carcass approach—vs. using the concentration of metabolizable energy of the diet—diet approach. The culprit of this disconnection might be related to how energy losses that are associated with supporting energy-expending processes (HiEv) are allocated between these approaches. When computing kG, the diet approach likely assigns the HiEv to the RE pool, whereas the carcass approach ignores the HiEV, assigning it to the overall heat production that is used to support the tissue metabolism. Opportunities exist for improving the California Net Energy System regarding the relationships of RE and RP in computing the requirements for energy and protein by growing cattle, but procedural changes might be needed such as increased accuracy in the determination of body composition and better partitioning of energy.


2004 ◽  
Vol 33 (7) ◽  
pp. 1125-1131 ◽  
Author(s):  
G.Louis Smith ◽  
Bruce A. Wielicki ◽  
Bruce R. Barkstrom ◽  
Robert B. Lee ◽  
Kory J. Priestley ◽  
...  
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2010 ◽  
Author(s):  
Susan Thomas ◽  
K. J. Priestley ◽  
N. M. Smith ◽  
N. G. Loeb ◽  
P. C. Hess ◽  
...  
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2021 ◽  
Vol 13 (21) ◽  
pp. 4464
Author(s):  
Jiawen Xu ◽  
Xiaotong Zhang ◽  
Chunjie Feng ◽  
Shuyue Yang ◽  
Shikang Guan ◽  
...  

Surface upward longwave radiation (SULR) is an indicator of thermal conditions over the Earth’s surface. In this study, we validated the simulated SULR from 51 Coupled Model Intercomparison Project (CMIP6) general circulation models (GCMs) through a comparison with ground measurements and satellite-retrieved SULR from the Clouds and the Earth’s Radiant Energy System, Energy Balanced and Filled (CERES EBAF). Moreover, we improved the SULR estimations by a fusion of multiple CMIP6 GCMs using multimodel ensemble (MME) methods. Large variations were found in the monthly mean SULR among the 51 CMIP6 GCMs; the bias and root mean squared error (RMSE) of the individual CMIP6 GCMs at 133 sites ranged from −3 to 24 W m−2 and 22 to 38 W m−2, respectively, which were higher than those found between the CERES EBAF and GCMs. The CMIP6 GCMs did not improve the overestimation of SULR compared to the CMIP5 GCMs. The Bayesian model averaging (BMA) method showed better performance in simulating SULR than the individual GCMs and simple model averaging (SMA) method, with a bias of 0 W m−2 and an RMSE of 19.29 W m−2 for the 133 sites. In terms of the global annual mean SULR, our best estimation for the CMIP6 GCMs using the BMA method was 392 W m−2 during 2000–2014. We found that the SULR varied between 386 and 393 W m−2 from 1850 to 2014, exhibiting an increasing tendency of 0.2 W m−2 per decade (p < 0.05).


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