Treffer: CSESpy: A Unified Framework for Data Analysis of the Payloads on Board the CSES Satellite.

Title:
CSESpy: A Unified Framework for Data Analysis of the Payloads on Board the CSES Satellite.
Source:
Remote Sensing; Oct2025, Vol. 17 Issue 20, p3417, 30p
Database:
Complementary Index

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Highlights: What are the main findings? A new Python package, CSESpy, which provides interfaces and tools for handling data from the ionospheric CSES mission, is introduced CSESpy features advanced analysis and visualization capabilities for multi-instrument measurements within a unified framework. What is the implication of the main finding? CSESpy enhances researchers' ability to study complex ionospheric phenomena by simplifying data handling and enabling multi-variable analysis of both space weather and seismic events. CSESpy flexible architecture supports integration with external datasets and embedding in wider software ecosystems. The China Seismo Electromagnetic Satellite (CSES) mission provides in situ measurements of the electromagnetic field, plasma, and charged particles in the topside ionosphere. Each CSES spacecraft carries several different scientific payloads delivering a wealth of information about the ionospheric plasma dynamics and properties, as well as measurement about energetic particles precipitating in the ionosphere. In this work, we introduce CSESpy, a Python package designed to provide an interface to CSES data products, with the aim of easing the pathway for scientists to carry out analyses of CSES data. Beyond simply being an interface to the data, CSESpy aims to provide higher-level analysis and visualization tools, as well as methods for combining concurrent measurements from different instruments, so as to allow multipayload studies in a unified framework. Moreover, CSESpy is designed to be highly flexible as such, it can be extended to interface with datasets from other sources and can be embedded in wider software ecosystems. We highlight some applications, also demonstrating that CSESpy is a powerful visualization tool for investigating complex events involving variations across multiple physical observables. [ABSTRACT FROM AUTHOR]

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