Managing vast volumes of climate data, often reaching into terabytes and petabytes, presents significant challenges in terms of storage, accessibility, efficient analysis, and on-the-fly interactive visualization. Traditional data handling techniques are increasingly inadequate for the massive atmospheric and oceanic data generated by modern climate research. We tackled these challenges by reorganizing the native data layout to optimize access and processing, implementing advanced visualization algorithms like OpenVisus for real-time interactive exploration, and extracting comprehensive metadata for all available fields to improve data discoverability and usability. Our work utilized extensive datasets, including downscaled projections of various climate variables and high-resolution ocean simulations from NEX GDDP CMIP6 and NASA DYAMOND datasets. By transforming the data into progressive, streaming-capable formats and incorporating ARCO (Analysis Ready, Cloud Optimized) features before moving them to the cloud, we ensured that the data is highly accessible and efficient for analysis, while allowing direct access to data subsets in the cloud. The direct integration of the Python library called Xarray allows efficient and easy access to the data, leveraging the familiarity most climate scientists have with it. This approach, combined with the progressive streaming format, not only enhances the findability, shareability and reusability of the data but also facilitates sophisticated analyses and visualizations from commodity hardware like personal cell phones and computers without the need for large computational resources. By collaborating with climate scientists and domain experts from NASA Jet Propulsion Lab and NASA Ames Research Center, we published more than 2 petabytes of climate data via our interactive dashboards for climate scientists and the general public. Ultimately, our solution fosters quicker decision-making, greater collaboration, and innovation in the global climate science community by breaking down barriers imposed by hardware limitations and geographical constraints and allowing access to sophisticated visualization tools via publicly available dashboards.