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Regridding Coefficient Estimates in Solar Radiation Analysisby@quantification
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Regridding Coefficient Estimates in Solar Radiation Analysis

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The appendix unveils regridding coefficient estimates in solar radiation analysis, detailing author contributions, competing interests, and financial support. Explore the statistical analyses and author roles, gaining insights into the significance of regridding in advancing solar energy research.
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Authors:

(1) Maggie D. Bailey, Colorado School of Mines and National Renewable Energy Lab;

(2) Douglas Nychka, Colorado School of Mines;

(3) Manajit Sengupta, National Renewable Energy Lab;

(4) Aron Habte, National Renewable Energy Lab;

(5) Yu Xie, National Renewable Energy Lab;

(6) Soutir Bandyopadhyay, Colorado School of Mines.

Table of Links

Abstract and Intro

Data

Bayesian Hierarchical Model (BHM)

Solar Radiation Example

Results

Conclusion

Appendix A: Simulation Study

Appendix B: Regridding Coefficient Estimates

References

Appendix B: Regridding Coefficient Estimates

Figure B1. Coefficient estimates for the intercept and each RCM for each month considered between the two methods.




Figure B2. Standard error of the coefficient estimates for the intercept and each RCM for each month considered between the two methods.



Author contributions. MDB conducted all statistical analyses and wrote the manuscript; SB and DN contributed to the manuscript and advised on all statistical analyses; MS, AH, and YX provided expertise in the application to solar radiation.


Competing interests. The contact author has declared that none of the authors has any competing interests.


Financial support. Funding provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Solar Energy Technologies Office.


Acknowledgements. This work was authored by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes.


This paper is available on arxiv under CC 4.0 license.