In this paper, we introduce a web-based visual analytics framework for democratizing advanced visualization and analysis capabilities pertinent to large-scale earth system simulations. We address the most significant limitations of present climate data analysis tools such as tightly coupled dependencies, inefficient data movements, complex user interfaces, and static visualizations. By developing a web-based visual analytics framework, we remove critical barriers to widespread accessibility and adoption of advanced scientific techniques. Through distributed connections to parallel diagnostics, we minimize data movements and leverage HPC platforms. The distributed framework also alleviates system dependency issues by employing a flexible RESTful interface. We embrace the visual analytics paradigm via new visual navigation techniques for hierarchical parameter spaces, multi-scale statistical views, and interactive spatio-temporal data mining methods that preserve details. Although generalizable to other science domains, the current work focuses on improving exploratory analysis of large-scale Community Land Model (CLM) and Community Atmosphere Model (CAM) simulations.