Principal Investigator (PI): Hook Hua, NASA's Jet Propulsion Laboratory

We will develop a distributed service-oriented tool that will be used to study long-term and global-scale trends in climate, water and energy cycle, and weather variability. We will provide to the community a Web Services tool that enables scientists to access the NEWS Level 2 data merged from multiple instruments in the NASA's A-Train satellite constellation and to customize the conditional subsetting of the Level 2 data and the production of Level 3 data from pre-summarized Level 3 data according to their specific needs.

We will facilitate the transparent access and manipulation of heterogeneous and distributed data by science users via Web Services on a multitude of programming environments. The tool will be comprised of (1) algorithms that subset Level 2 data and generate and transform Level 3 data, (2) Web Services that expose the algorithms and facilitate data access, (3) client-side modules that enable users to discover, access, and manipulate the distributed data, and (4) data crawler and catalog. We will demonstrate the applicability of the proposed tool in studies of climate systems and climate change by capturing long-term global trends and covariabilities of multiple instrument data from A-Train satellite constellation. This work directly addresses the objectives of the Advancing Collaborative Connections for Earth System Science (ACCESS) solicitation in three ways.

First we will improve NASA Earth science data interoperability to facilitate the transparent access and manipulating of heterogeneous and distributed data by providing a Web Services tool that enables science users to access merged data from multi-instuments in the NASA's A-Train satellite constellation. A-Train sensor data provides detailed record of simultaneous observations of temperature, water vapor and cloud properties. Currently there does not exist a capability to discover and access data from multiple instruments in the A-Train as merged multi-parameter data sets.

Second, we will increase users' ability to customize their discovery, access, delivery, and manipulation of NASA Earth science data by providing a Web Services tool that allows science users to customize the conditional subsetting of Level 2 data and the production of Level 3 data on a multiple of programming environments. We will create client-side modules that are general enough to encompass various needs of scientists and are easy to interface with the scientific code that science users are using.

Third, we will deploy existing Earth science research analysis tools and software using a web-based Service Oriented Architecture paradigm by deploying a well-established statistical summarization tool as a Web Service. The summarization tool produces Level 3 data that preserve the critical instantaneous relationship between parameters and comprehensively characterize the long-term and global-scale trends and covariablity of multiple parameters.