A method for filling gaps in solar irradiance and in solar proxy data

TL;DR

The paper presents a robust, data-adaptive method based on iterative singular value decomposition for filling gaps in solar irradiance and proxy data, improving data completeness for spectral analysis.

Contribution

Introduces a novel nonparametric, self-consistent gap-filling method using iterative SVD that handles multi-wavelength and proxy data with minimal tuning.

Findings

Effective in filling gaps in solar EUV observations

Applicable to solar proxy data for composite building

Robust across different time scales

Abstract

Data gaps are ubiquitous in spectral irradiance data, and yet, little effort has been put into finding robust methods for filling them. We introduce a data-adaptive and nonparametric method that allows us to fill data gaps in multi-wavelength or in multichannel records. This method, which is based on the iterative singular value decomposition, uses the coherency between simultaneous measurements at different wavelengths (or between different proxies) to fill the missing data in a self-consistent way. The interpolation is improved by handling different time scales separately. Two major assets of this method are its simplicity, with few tuneable parameters, and its robustness. Two examples of missing data are given: one from solar EUV observations, and one from solar proxy data. The method is also appropriate for building a composite out of partly overlapping records.