Payloads for investigations of Satial and Temporal Variability of Ocean and Ice Conditions in and Near the Marginal Ice Zone

Lead PI: Dr. Christopher J. Zappa

Unit Affiliation: Ocean and Climate Physics, Lamont-Doherty Earth Observatory (LDEO)

October 2013 - August 2015
Inactive
Arctic Ocean
Project Type: Research

DESCRIPTION: Despite the significance of the marginal ice zones of the Arctic Ocean, basic parameters such as sea surface temperature (SST) and a range of sea-ice characteristics are still insufficiently understood in these areas, and especially so during the summer melt period. The field campaigns summarized here, identified collectively as the “Marginal Ice Zone Ocean and Ice Observations and Processes Experiment” (MIZOPEX), were funded by U.S. National Aeronautic and Space Administration (NASA) with the intent of helping to address these information gaps through a targeted, intensive observation field campaign that tested and exploited unique capabilities of multiple classes of unmanned aerial systems (UASs). MIZOPEX was conceived and carried out in response to NASA’s request for research efforts that would address a key area of science while also helping to advance the application of UASs in a manner useful to NASA for assessing the relative merits of different UASs. To further exercise the potential of unmanned systems and to expand the science value of the effort, the field campaign added further challenges such as air deployment of miniaturized buoys and coordinating missions involving multiple aircraft. Specific research areas that MIZOPEX data were designed to address include relationships between ocean skin temperatures and subsurface temperatures and how these evolve over time in an Arctic environment during summer; variability in sea-ice conditions such as thickness, age, and albedo within the marginal ice zone (MIZ); interactions of SST, salinity, and ice conditions during the melt cycle; and validation of satellite-derived SST and ice concentration fields provided by satellite imagery and models.