With the tendency of growing data sets generated by large-scale simulation models utilizing massively parallel supercomputers, in-situ visualization can be a way to avoid bottlenecks. Enabling in-situ visualization in a simulation model ask for special attention to the interface between a parallel simulation model and the data analysis part of the visualization, and to the presentation and interaction scenarios. The modifications in the scientific workflows potentially results in a paradigm shift, which affects compute and data intensive applications generally. We present our approach for enabling in-situ visualization within the highly parallelized climate model ICON using the DSVR visualization framework. We focus on the requirements for a generalized grid and data structures, and for universal, scalable algorithms for volume and flow visualization of time series. While the integration of a new isosurface extraction into ICON is still work in progress, we integrated pathline extraction as a technique for the visualization of unsteady flows into ICON.