Abstract
The Distributed Oceanographic Match-up Service (DOMS) provides a visionary approach to on-demand, programmatic collocation of satellite and in situ observations to support a range of user communities. DOMS provides both application programming and graphical user interfaces, which allow users to input a series of geospatial references for satellite observations and receive in situ observations that are matched to the satellite data within the selected search domain and according to user-specified match-up tolerances. By leveraging MapReduce, NoSQL, and distributed geospatial subsetting technologies, DOMS presents a new approach for large-scale data match up that can take advantage of the elasticity of cloud computing environments. In its first instance, DOMS supports data matching for sea surface temperature, sea surface salinity, and ocean winds using satellite data from the Multiscale Ultrahigh Resolution (MUR) Sea Surface Temperature Level 4, Soil Moisture Active Passive (SMAP) Level 2, and Advanced Scatterometer (ASCAT)-B Level 2 products, respectively. In situ observations are currently provided from the Salinity Processes in the Upper Ocean Regional Study (SPURS) 1 field experiment, International Comprehensive Ocean-Atmosphere Data Set (ICOADS), and Shipboard Automated Meteorological and Oceanographic System (SAMOS) initiative. The distributed data and software design allows flexibility in defining search parameters and the ability to modify and update searches without the need to redesign or rewrite one-off data matching software. The overall horizontal-scale architecture, workflow, and initial configuration of DOMS for undertaking distributed and computationally costly, on-demand processing are described. The authors note the strengths and limitations of the initial design and implementation and outline plans to enhance and improve DOMS through additional integration projects.
| Original language | English |
|---|---|
| Title of host publication | Big Data Analytics in Earth, Atmospheric, and Ocean Sciences |
| Publisher | wiley |
| Pages | 189-214 |
| Number of pages | 26 |
| ISBN (Electronic) | 9781119467557 |
| ISBN (Print) | 9781119467571 |
| DOIs | |
| State | Published - Nov 1 2022 |
Keywords
- Application program interfaces
- DOMS file output
- Distributed oceanographic match-up service
- Earth-science big data
- Match-up algorithms
- Multiscale ultrahigh resolution
- NEXUS
- Satellite data
- System architecture
- Web-based graphical user interface