Climate Data Analysis Tools (CDAT)
Climate Data Analysis Tools (CDAT) is a software infrastructure that uses an object-oriented scripting language to link together separate software subsystems and packages thus forming an integrated environment for solving model diagnosis problems. The power of the system comes from Python and its ability to seamlessly interconnect software. Python provides a general purpose and full-featured scripting language with a variety of user interfaces including command-line interaction, stand-alone scripts (applications) and graphical user interfaces (GUI). The CDAT subsystems, implemented as modules, provide access to and management of gridded data (Climate Data Management System or CDMS); large-array numerical operations (Numerical Python); and visualization (Visualization and Control System or VCS).
One of the most difficult challenges facing climate researchers today is the cataloging and analysis of massive amounts of multi-dimensional global atmospheric and oceanic model data. To reduce the labor intensive and time-consuming process of data management, retrieval, and analysis, PCMDI and other DOE sites have come together to develop intelligent filing system and data management software for the linking of storage devices located throughout the United States and the international climate research community. This effort, headed by PCMDI, NCAR, and ANL will allow users anywhere to remotely access this distributed multi-petabyte archive and perform analysis. PCMDI's CDAT is an innovative system that supports exploration and visualization of climate scientific datasets. As an "open system", the software sub-systems (i.e., modules) are independent and freely available to the global climate community. CDAT is easily extended to include new modules and as a result of its flexibility, PCMDI has integrated other popular software components, such as: the popular Live Access Server (LAS) and the Distributed Oceanographic Data System (DODS). Together with ANL's Globus middleware software, CDAT's focus is to allow climate researchers the ability to access and analyze multi-dimensional distributed climate datasets.
Climate Model Output Rewriter (CMOR)
The "Climate Model Output Rewriter" (CMOR, pronounced "Seymour") comprises a set of FORTRAN 90 functions that can be used to produce CF-compliant netCDF files that fulfill the requirements of many of the climate community's standard model experiments. These experiments are collectively referred to as MIP's and include, for example, AMIP, CMIP, CFMIP, PMIP, APE, and IPCC scenario runs. The output resulting from CMOR is "self-describing" and facilitates analysis of results across models.
Much of the metadata written to the output files is defined in MIP-specific tables, typically made available from each MIP's web site. CMOR relies on these tables to provide much of the metadata that is needed in the MIP context, thereby reducing the programming effort required of the individual MIP contributors.