Geomagnetic Time Series and Correlation Coefficients for Space Weather, 1997-2013

1997-2013 geomagnetic time series for four SuperMAG stations, processed into membership scores and correlation coefficients. The dataset supports reproducibility for a study analyzing correlation in intuitionistic fuzzy metric spaces. It was created by Mudassira Mustafa and last updated in April 2026.

Use Cases

• Replicating scale-dependent correlation analysis based on the described intuitionistic fuzzy metric space (IFMS) methods.
• Comparing classical, fuzzy, and IFMS correlation coefficients for geomagnetic parameters over annual and multi-year blocks.
• Analyzing convergence of geomagnetic data correlations using the provided nearness (M) and non-nearness (N) values.
• Studying geomagnetic field variations (X, Y, Z components) from specific ground stations between 1997 and 2013.

Strengths

• Clear temporal coverage from 1997 to 2013 for the core time-series data.
• Includes processed data for four distinct analysis outputs: raw components, membership scores, correlation coefficients, and convergence metrics.
• Explicitly documents the mathematical transformations (min-max normalization, score series s = μ - ν) applied to the data.
• Small size (220.5 KB) facilitates quick download and inspection.

Limitations

• Row count is unknown, which may limit suitability assessment for large-scale modeling.
• Column-level documentation is absent; field semantics must be inferred after download.
• Geographic coverage is limited to four specific SuperMAG ground stations.

Provenance

Source

SuperMAG collaborative network (https://supermag.jhuapl.edu/)

Collection Method

Raw geomagnetic data were obtained from SuperMAG and processed (min-max normalization, membership/non-membership computation) for the associated study.

Time Range

1997-2013

Freshness

Last updated 2026-04-28 09:57:56; freshness should be verified.

Geography

Data from four SuperMAG stations: Alibag (ABG), Addis Ababa (AAE), Amsterdam (AMS), and Argentine Islands (AIA).