Spatial characterization of the meltwater field from icebergs in the Weddell Sea

• Published in: Proceedings of the National Academy of Sciences
• Main Authors: Helly, John J., Kaufmann, Ronald S., Vernet, Maria, Stephenson, Gordon R.
• Format: Text
• Language: English
• Published: National Academy of Sciences 2011
• Subjects: Spatial Cyberinfrastructure Special Feature; Peta; Southern Ocean; Weddell; Weddell Sea
• Online Access: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3078385; http://www.ncbi.nlm.nih.gov/pubmed/21444769; https://doi.org/10.1073/pnas.0909306108

We describe the results from a spatial cyberinfrastructure developed to characterize the meltwater field around individual icebergs and integrate the results with regional- and global-scale data. During the course of the cyberinfrastructure development, it became clear that we were also building an integrated sampling planning capability across multidisciplinary teams that provided greater agility in allocating expedition resources resulting in new scientific insights. The cyberinfrastructure-enabled method is a complement to the conventional methods of hydrographic sampling in which the ship provides a static platform on a station-by-station basis. We adapted a sea-floor mapping method to more rapidly characterize the sea surface geophysically and biologically. By jointly analyzing the multisource, continuously sampled biological, chemical, and physical parameters, using Global Positioning System time as the data fusion key, this surface-mapping method enables us to examine the relationship between the meltwater field of the iceberg to the larger-scale marine ecosystem of the Southern Ocean. Through geospatial data fusion, we are able to combine very fine-scale maps of dynamic processes with more synoptic but lower-resolution data from satellite systems. Our results illustrate the importance of spatial cyberinfrastructure in the overall scientific enterprise and identify key interfaces and sources of error that require improved controls for the development of future Earth observing systems as we move into an era of peta- and exascale, data-intensive computing.