| Autor: |
Quigley, Patricia A., Unal, Resit, Stackhouse Jr., Paul W., Cox, Stephen J. |
| Předmět: |
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| Zdroj: |
Proceedings of the 2017 International Annual Conference of the American Society for Engineering Management; 2018, p1-9, 9p |
| Abstrakt: |
Earth's Radiation Budget (ERB) is an accounting of all incoming energy from the sun and outgoing energy reflected and radiated to space by earth's surface and atmosphere. ERB data collection and measurement poses a major scientific and engineering challenge. The National Aeronautics and Space Administration (NASA)/Global Energy and Water Cycle Experiment (GEWEX) Surface Radiation Budget (SRB) project produces and archives long-term datasets representative of this energy exchange system on a global scale. Ground sites are capable of obtaining direct measurements of all of the components of the SRB, but it would be very costly to cover the entire globe wth ground sites. Therefore, satellites are utilized to acquire data where ground sites would be impractical. The problem is that surface irradiance cannot be directly measured by satellites, so it must be derived from a variety of satellite assimilation products and acquired atmospheric data. This study utilized design of experiments to aid engineering managers in identifying key predictor variables and their interactions for 14 shortwave radiative components of the atmosphere that are produced by the SRB algorithm. A D-Optimal design was chosen to study SRB inputs consisting of 13 atmospheric properties from a sample geological location. This enabled a 313 full factorial design of experiments to be reduced from over 1.6M to 128. Second order response surface models were constructed from the results of a regression analysis to determine the most influential input variables and two-factor interactions. This approach may enable scientists and engineering managers in collecting and analyzing satellite data for Earth's Radiation Budget. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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