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The oceanographic community continues to need a generalized data collocation capability for satellite and/or in situ observations that is publicly accessible and provides flexibility and reproducibility for use cases ranging from open science to satellite retrieval calibration and validation. The Cloud-based Data Match-Up Service (CDMS) is a collaborative effort between NASA JPL, COAPS, NCAR, and Saildrone to address this need. With an exponential increase in the volume of satellite data, the CDMS architecture is designed to be scalable and to leverage the elasticity of the cloud. The differences between remote sensing data at various data processing levels and the heterogeneous nature of in situ data makes developing a generic system challenging, but CDMS is designed with the consideration of making it possible to efficiently onboard new datasets. Asynchronous processing serves as a critical component of the CDMS architecture to allow for efficient handling of large data requests. In addition to an overview of CDMS, the authors will demonstrate the asynchronous processing to address and analyze wind to SST relationships during an ocean heat wave.

There is a need in the oceanographic community for a generalized match-up capability that is publicly accessible and provides flexibility and reproducibility for use cases ranging from Ocean Science to satellite retrieval calibration and validation. The Cloud-based Data Match-Up Service (CDMS) is a collaborative effort between NASA JPL, COAPS, NCAR, and Saildrone to address this need. This talk will demonstrate the present and planned capabilities of CDMS. CDMS is an extension of the Distributed Oceanographic Match-Up Service (DOMS) which was funded by the NASA AIST program, with additional support now under NASA ACCESS to deliver a production-ready match-up capability that fully leverages cloud-native services and is ready for infusion at data archive centers and with other projects. CDMS provides a mechanism for users to input a series of geospatial references for satellite datasets and receive the in situ or satellite observations that are collocated based on provided temporal and spatial ranges. CDMS eliminates the need for one-off match-up programs that require satellite and in situ data to be housed locally as the computation occurs in the cloud and supports connectivity to remote data providers via a common set of interfaces and protocols. CDMS exposes a number of HTTP API endpoints, allowing users to execute match-up requests from their desired programming environment. The software stack that enables the CDMS match-up capability is available via the Apache Science Data Analytics Platform (SDAP) which is an Apache incubator project. This poster was presented at the July 2022 ESIP Meeting, held in Pittsburgh, PA..

The Cloud-based Data Match-Up Service (CDMS) is a collaborative effort between NASA JPL, COAPS, NCAR, and Saildrone. CDMS is an extension of the Distributed Oceanographic Match-Up Service (DOMS) which was funded by the NASA AIST program. CDMS will provide a mechanism for users to input a series of geospatial references for satellite observations and receive the in situ or satellite observations that are matched to the primary satellite data within selectable temporal and spatial search domains. This presentation was given at the 2022 NASA ESDSWG Meeting (April 19-21, 2022).

The Cloud-based Data Match-Up Service (CDMS) is a collaborative effort between NASA JPL, COAPS, NCAR, and Saildrone. CDMS is an extension of the Distributed Oceanographic Match-Up Service (DOMS) which was funded by the NASA AIST program. CDMS will provide a mechanism for users to input a series of geospatial references for satellite observations and receive the in situ or satellite observations that are matched to the primary satellite data within selectable temporal and spatial search domains. The software stack that enables CDMS match-up capability is available via the Apache Science Data Analytics Platform (SDAP), which is an Apache incubator project. Under the ACCESS program, the team plans to deliver a production-ready match-up capability that fully leverages cloud-native services.This poster was presented at the 2021 Earth Science Information Partners (ESIP) Summer Meeting held virtually in July 2021.