Abstract: A reanalysis ensemble service includes a plurality of conversion utilities, each conversion utility configured to convert a specific one of a plurality of disparate climate reanalysis datasets from different sources to common format files that are temporally and spatially registered, a data analytics platform for storing and operating on the different sourced common format files, a service interface for mapping service requests to analytic operations performed on the different sourced common format files by the data analytics platform, and a services library that dynamically creates data objects from one or more of the different sourced common format files in response to the analytic operations, and delivers the data objects to the service interface.

Abstract: A climate data intercomparison and analytics service application programming interface (CDIAS-API) includes a set of basic utilities configured to map calls from client applications to single service-side methods operating on one or more disparate climate reanalysis datasets by the climate data intercomparison and analytics service, a set of extended utilities comprising scripts that call on one or more of a set of canonical operations, and one or more basic utilities, and a collections reference model configured to provide semantic alignment of variable names, method alignment of statistical operations, and output data format consistency for operations across the one or more disparate climate reanalysis datasets.

Abstract: An extended reanalysis ensemble service includes a loader services application program interface configured to receive data parameters for a set of automated multisource data provisioning operations, provide climate source data from one or more disparate climate data collections specified in the data parameters to conversion utilities for transforming the climate source data into flat, serialized block compressed sequence files, and load the sequence files to a distributed file system of the extended reanalysis ensemble service, and a reanalysis ensemble service application program interface configured to receive operational parameters for the set of automated multisource data provisioning operations, convert the operational parameters to one or more methods recognized by a service interface of the extended reanalysis ensemble service to be converted to analytical operations executed by the extended reanalysis ensemble service, and provide results of the one or more analytical operations executed by the exten

Abstract: A reanalysis ensemble service includes a plurality of conversion utilities, each conversion utility configured to convert a specific one of a plurality of disparate climate data collections from different sources to common format files that are temporally and spatially registered, where the disparate climate data collections include reanalysis data sets and forward processing data products, a data analytics platform for storing and operating on the different sourced common format files, a service interface for mapping service requests to analytic operations performed on the different sourced common format files by the data analytics platform, and a services library that dynamically creates data objects from one or more of the different sourced common format files in response to the analytic operations, and delivers the data objects to the service interface.

Abstract: A system, method and computer-readable storage devices for providing an interface for an analytic service for Modern-Era Retrospective Analysis for Research and Applications (MERRA) datasets. An example system for providing the service includes a data analytics platform of an assemblage of compute and storage nodes that provide a compute-storage fabric upon which high-performance parallel operations are performed over a collection of climate data stored in a distributed file system, a sequencer that transforms the climate data, a desequencer that transforms serialized block compressed sequence files between data formats. The system includes a services library of applications that dynamically create data objects from the data as reduced final results, and a utilities library of software applications that process flat serialized block compressed sequence files. The system also includes a service interface through which a client device can access the climate data via the data analytics platform.

Abstract: A system, method and computer-readable storage devices for providing a climate data analytic services application programming interface. The system includes a programming library that enables client device software to invoke the capabilities of a climate data analytics system through requests to various services supported by the climate data analytics system, and also includes a client-side communications interface that enables the programming library's methods to interact with a climate data analytics system's server interface to obtain access to the capabilities of the system. In one implementation, the programming library is implemented in the Python programming language.

Abstract: A system, method and computer-readable storage devices for providing a climate data persistence service. A system configured to provide the service can include a climate data server that performs data and metadata storage and management functions for climate data objects, a compute-storage platform that provides the resources needed to support a climate data server, provisioning software that allows climate data server instances to be deployed as virtual climate data servers in a cloud computing environment, and a service interface, wherein persistence service capabilities are invoked by software applications running on a client device. The climate data objects can be in various formats, such as International Organization for Standards (ISO) Open Archival Information System (OAIS) Reference Model Submission Information Packages, Archive Information Packages, and Dissemination Information Packages.

Abstract: A system, method and computer-readable storage devices for providing an interface for an analytic service for Modern-Era Retrospective Analysis for Research and Applications (MERRA) datasets. An example system for providing the service includes a data analytics platform of an assemblage of compute and storage nodes that provide a compute-storage fabric upon which high-performance parallel operations are performed over a collection of climate data stored in a distributed file system, a sequencer that transforms the climate data, a desequencer that transforms serialized block compressed sequence files between data formats. The system includes a services library of applications that dynamically create data objects from the data as reduced final results, and a utilities library of software applications that process flat serialized block compressed sequence files. The system also includes a service interface through which a client device can access the climate data via the data analytics platform.

Abstract: A system, method and computer-readable storage devices for providing climate data analytics as a service. An example system can include a high-performance data analytics platform that provides a compute-storage fabric, a high-performance file system, and a virtualizer. The system can include an analytic service that transforms multidimensional binary climate data to yield analysis files formatted for high-performance analytic software input and output, that transforms analysis files to yield multidimensional binary files encoded in a commonly used climate data file format, and that performs high-performance analytic operations over analysis files stored in the high-performance files system and collects results into dynamically created data objects.. The system can also provide a persistence service and a system interface. The persistence service can store and manage the data objects, and can deploy climate data server instances as virtual climate data servers in a federated data grid.

Abstract: A system, method and computer-readable storage devices for providing a climate data analytic services application programming interface. The system includes a programming library that enables client device software to invoke the capabilities of a climate data analytics system through requests to various services supported by the climate data analytics system, and also includes a client-side communications interface that enables the programming library's methods to interact with a climate data analytics system's server interface to obtain access to the capabilities of the system. In one implementation, the programming library is implemented in Python.

Abstract: A system, method and computer-readable storage devices for providing a climate data persistence service. A system configured to provide the service can include a climate data server that performs data and metadata storage and management functions for climate data objects, a compute-storage platform that provides the resources needed to support a climate data server, provisioning software that allows climate data server instances to be deployed as virtual climate data servers in a cloud computing environment, and a service interface, wherein persistence service capabilities are invoked by software applications running on a client device. The climate data objects can be in various formats, such as International Organization for Standards (ISO) Open Archival Information System (OAIS) Reference Model Submission Information Packages, Archive Information Packages, and Dissemination Information Packages.

Abstract: A system, method and computer-readable storage devices for providing a climate data analytic services application programming interface distribution package. The example system can provide various components. The system provides a climate data analytic services application programming interface library that enables software applications running on a client device to invoke the capabilities of a climate data analytic service. The system provides a command-line interface that provides a means of interacting with a climate data analytic service by issuing commands directly to the system's server interface. The system provides sample programs that call on the capabilities of the application programming interface library and can be used as templates for the construction of new client applications. The system can also provide test utilities, build utilities, service integration utilities, and documentation.