Abstract

This study provides an exhaustive examination of the evolution of sunspot number (SSN) observations within Egypt, a nation celebrated for its profound astronomical legacy. Although Egypt has a well-established tradition of solar observation, the local SSN records spanning from 2010 to 2022 are compromised by a considerable frequency of absent data, thereby presenting substantial challenges to the precise assessment of solar activity. Addressing this challenge, the study employs dynamic time warping (DTW) as a methodological tool to assess the alignment of local and global SSN datasets. This technique adeptly harmonizes these datasets by reconciling temporal inconsistencies and variations in sampling rates. Subsequent to the application of DTW, the research integrates orthogonal regression for the imputation of the absent values in the Egyptian SSN dataset. This method, preferred for its proficiency in managing errors in both the dependent and independent variables, deviates from conventional linear regression techniques, thereby providing a more nuanced approach to data approximation. The investigation delineates a noteworthy statistical association between the locally-estimated SSN values and the global SSN indices. This correlation is characterized by a consistent pattern in which the locally-derived SSN are systematically lower in comparison to their global counterparts. Nevertheless, these local values display parallel trends and seasonal fluctuations akin to those observed in the global dataset, validating the imputation method and highlighting the unique characteristics of the Egyptian SSN data within the global context of solar activity monitoring. The implications of these findings are significant for the discipline of solar physics, especially for regions contending with incomplete datasets. The methodologies advanced in this research offer a robust framework for the enhancement of datasets with missing data, thus broadening the comprehension of solar phenomena.

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