Towards Simpler Custom and OpenSearch Services for Voluminous NEWS Merged A-Train Data (Invited)

To simplify access to large and complex satellite data sets for climate analysis and model verification, we developed web services that is used to study long-term and global-scale trends in climate, water and energy cycle, and weather variability. A related NASA Energy and Water Cycle Study (NEWS) task has created a merged NEWS Level 2 data from multiple instruments in NASA’s A-Train constellation of satellites. We used this data to enable creation of climatologies that include correlation between observed temperature, water vapor and cloud properties from the A-Train sensors. Instead of imposing on the user an often rigid and limiting web-based analysis environment, we recognize the need for simple and well-designed services so that users can perform analysis in their own familiar computing environments. Custom on-demand services were developed to improve data accessibility of voluminous multi-sensor data. Services enabling geospatial, geographical, and multi-sensor parameter subsets of the data, as well a custom time-averaged Level 3 service will be presented. We will also show how a Level 3Q data reduction approach can be used to help “browse” the voluminous multi-sensor Level 2 data. An OpenSearch capability with full text + space + time search of data products will also be presented as an approach to facilitated interoperability with other data systems. We will present our experiences for improving user usability as well as strategies for facilitating interoperability with other data systems.