This paper introduces a lidar and radar meteorology science gateway deployed on the NSF Jetstream2 cloud, designed to enhance educational and research activities in atmospheric science. Utilizing the "Zero to JupyterHub with Kubernetes" workflow, we have created a science gateway that integrates lidar and radar meteorology software packages, notably the Lidar Radar Open Software Environment (LROSE). This integration allows users to execute applications directly from the JupyterLab terminal, streamlining the creation of datasets for further anal- ysis and visualization within Jupyter notebooks. By combining traditional command-line operations with modern Python-based tools for data analysis and visualization, this gateway provides a robust end-to-end solution that caters to both educational and research needs. The gateway has already been vital in facilitating LROSE instructional workshops and will see future enhancements such as GPU acceleration to boost performance. Our work demonstrates the significant potential of merging established scientific computing techniques with advanced Python environments, opening new avenues for computational science education and research.