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Abstract. We report the first observations of continuum emission at the poleward boundary of the dayside auroral oval. Spectral measurements of high-latitude continuum emissions resemble those of Strong Thermal Emission Velocity Enhancement (STEVE), with light characterized by colours such as white, pale pink, or mauve. The emission enhancement spans the entire visible wavelength range. However, unlike STEVE, the high-latitude dayside continuum emission events tightly follow the auroral particle precipitation, often forming field-aligned rays and other dynamic shapes. Some dayside emissions appeared as wide arcs or cloud-like structures within the red-emission-dominated dayside aurora. Our spectral measurements further suggest that the broadband continuum emission may extend into the near-infrared (NIR) regime. Similar to the STEVE emission, low-Earth-orbit measurements of plasma flow in the region of continuum emission show a strong horizontal cross-track velocity shear. Ground-based radar and optical observations provide evidence of both plasma and neutral heating, as well as upwelling, in connection to the continuum emissions. We conclude that the interplay between different heating mechanisms may be an important factor in generating high-latitude continuum emissions. 

In the space physics community, processing and combining observational and modeling data from various sources is a demanding task because they often have different formats and use different coordinate systems. The Python package GeospaceLAB has been developed to provide a unified, standardized framework to process data. The package is composed of six core modules, including DataHub as the data manager, Visualization for generating publication quality figures, Express for higher-level interfaces of DataHub and Visualization , SpaceCoordinateSystem for coordinate system transformations, Toolbox for various utilities, and Configuration for preferences. The core modules form a standardized framework for downloading, storing, post-processing and visualizing data in space physics. The object-oriented design makes the core modules of GeospaceLAB easy to modify and extend. So far, GeospaceLAB can process more than twenty kinds of data products from nine databases, and the number will increase in the future. The data sources include, e.g., measurements by EISCAT incoherent scatter radars, DMSP, SWARM, and Grace satellites, OMNI solar wind data, and GITM simulations. In addition, the package provides an interface for the users to add their own data products. Hence, researchers can easily collect, combine, and view multiple kinds of data for their work using GeospaceLAB. Combining data from different sources will lead to a better understanding of the physics of the studied phenomena and may lead to new discoveries. GeospaceLAB is an open source software, which is hosted on GitHub. We welcome everyone in the community to contribute to its future development.