Climate modeling seeks to create computational models that, based upon historical measurements, can predict future events and conditions. The models employed to reach these conclusions are often very complex, incorporating a large amount of data over many decades from a number of repositories. Making the calculations even more complex, many models correlate numerous physical properties (e.g. humidity, temperature, rainfall, and many, many more) to identify usable patterns and trends. The climate modeling efforts of this project revolve around the implementation and development of fine-scale, downscaling datasets based on transforming Global Clime Modeling products into space scales relevant for regional and local impact studies.
As with the other undertakings of the project, data generated by climate modeling efforts is made freely available for download by any interested party. Though many, terabytes of modeling data exist, a summary of that data is accessible from this page. Additional modeling information and data are available from Dr. John Mejia.