Regridding Uncertainty for Statistical Downscaling of Solar Radiation: Referencesby@quantification

Regridding Uncertainty for Statistical Downscaling of Solar Radiation: References

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This reference list compiles studies on climate data interpolation, covering challenges in precipitation forecast skill scores, the impact of spatial interpolation algorithms, and insights into spatial dynamics in climate research. It provides a diverse perspective on statistical analyses and considerations crucial for understanding and navigating climate data challenges.
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(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.

Abstract and Intro


Bayesian Hierarchical Model (BHM)

Solar Radiation Example



Appendix A: Simulation Study

Appendix B: Regridding Coefficient Estimates



Accadia, C., Mariani, S., Casaioli, M., Lavagnini, A., and Speranza, A.: Sensitivity of precipitation forecast skill scores to bilinear interpolation and a simple nearest-neighbor average method on high-resolution verification grids, Weather and forecasting, 18, 918–932, 2003.

Berndt, C. and Haberlandt, U.: Spatial interpolation of climate variables in Northern Germany—Influence of temporal resolution and network density, Journal of Hydrology: Regional Studies, 15, 184–202, 2018.

Chandler, R., Barnes, C., Brierley, C., and Alegre, R.: Regridding and interpolation of climate data for impacts modelling–some cautionary notes, Tech. rep., Copernicus Meetings, 2022.

Cressie, N. and Wikle, C. K.: Statistics for Spatio-Temporal Data, 2011.

Cressie, N. A.: Change of support and the modifiable areal unit problem, 1996.

Diaconescu, E. P., Gachon, P., and Laprise, R.: On the remapping procedure of daily precipitation statistics and indices used in regional climate model evaluation, Journal of Hydrometeorology, 16, 2301–2310, 2015.

Ensor, L. A. and Robeson, S. M.: Statistical characteristics of daily precipitation: comparisons of gridded and point datasets, Journal of Applied Meteorology and Climatology, 47, 2468–2476, 2008.

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Gelfand, A. E., Zhu, L., and Carlin, B. P.: On the change of support problem for spatio-temporal data, Biostatistics, 2, 31–45, 2001.

Handcock, M. S. and Stein, M. L.: A Bayesian analysis of kriging, Technometrics, 35, 403–410, 1993.

Harris, T., Li, B., and Sriver, R.: Multi-model Ensemble Analysis with Neural Network Gaussian Processes, arXiv [preprint] arXiv:2202.04152, 2022.

Loghmari, I., Timoumi, Y., and Messadi, A.: Performance comparison of two global solar radiation models for spatial interpolation purposes, Renewable and Sustainable Energy Reviews, 82, 837–844, 2018.

McGinnis, S. and Mearns, L.: Building a climate service for North America based on the NA-CORDEX data archive, Climate Services, 22, 100 233, 2021.

McGinnis, S., Mearns, L., and McDaniel, L.: Effects of Spatial Interpolation Algorithm Choice on Regional Climate Model Data Analysis, "Fall Meeting, American Geophysical Union, San Francisco", 2010.

Phillips, D. L. and Marks, D. G.: Spatial uncertainty analysis: propagation of interpolation errors in spatially distributed models, Ecological Modelling, 91, 213–229, 1996.

Rajulapati, C. R., Papalexiou, S. M., Clark, M. P., and Pomeroy, J. W.: The perils of regridding: examples using a global precipitation dataset, Journal of Applied Meteorology and Climatology, 60, 1561–1573, 2021.

Rauscher, S. A., Coppola, E., Piani, C., and Giorgi, F.: Resolution effects on regional climate model simulations of seasonal precipitation over Europe, Climate dynamics, 35, 685–711, 2010.

Sengupta, M., Xie, Y., Lopez, A., Habte, A., Maclaurin, G., and Shelby, J.: The national solar radiation data base (NSRDB), Renewable and sustainable energy reviews, 89, 51–60, 2018.

Whittemore, A. S.: Errors-in-variables regression using Stein estimates, The American Statistician, 43, 226–228, 1989.

This paper is available on arxiv under CC 4.0 license.