The accumulation and impacts in the ocean of marine debris generated by anthropogenic activities and aggravated by natural disasters are of growing concern, yet our existing data collection systems are rudimentary and cannot answer even fundamental questions. This is partly due to the diversity of the debris and the vastness of the ocean that complicate observations. The magnitude and complexity of the problem prompted NASA to sponsor a workshop to review existing and emerging technologies that could be capable to remotely survey the state of marine debris in the ocean. This workshop, held January 2016, brought together oceanographers, technologists, and experts in marine debris. In this paper we summarize the state-of-the-art of science and observations, and the stated goals of this workshop.

A preliminary attempt of deriving a purely satellite-based Temperature-Salinity (T-S) diagram is presented, with the overall aim of assessing to what extent is possible, and in which geographical areas, to identify and trace water masses by satellite. This has been performed by using recent SMOS and Aquarius satellite SSS products in conjunction with spaceborne SST data. A baseline T-S diagram is arranged from climatology data, differentiating 7 ocean zones and mapping them into the T-S domain. Therefore, a comparison with satellite data is carried out, highlighting, for this preliminary test, which are the most challenging zones and where, in turn, they mutually agree in a reasonable way.

This work investigates multiagent path planning in strong, dynamic currents using thousands of highly underactuated vehicles. We address the specific task of path planning for a global network of ocean-observing floats. These submersibles are typified by the Argo global network consisting of over 3000 sensor platforms. They can control their buoyancy to float at depth for data collection or rise to the surface for satellite communications. Currently, floats drift at a constant depth regardless of the local currents. However, accurate current forecasts have become available which present the possibility of intentionally controlling floats' motion by dynamically commanding them to linger at different depths. This project explores the use of these current predictions to direct float networks to some desired final formation or position. It presents multiple algorithms for such path optimization and demonstrates their advantage over the standard approach of constant-depth drifting.

Data collection using Autonomous Underwater Vehicles (AUVs) is increasing in importance within the oceanographic research community. Contrary to traditional moored or static platforms, mobile sensors require intelligent planning strategies to maneuver through the ocean. However, the ability to navigate to high-value locations and collect data with specific scientific merit is worth the planning efforts. In this study, we examine the use of ocean model predictions to determine the locations to be visited by an AUV, and aid in planning the trajectory that the vehicle executes during the sampling mission. The objectives are: a) to provide near-real time, in situ measurements to a large-scale ocean model to increase the skill of future predictions, and b) to utilize ocean model predictions as a component in an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. We present an algorithm designed to generate paths for AUVs to track a dynamically evolving ocean feature utilizing ocean model predictions. This builds on previous work in this area by incorporating the predicted current velocities into the path planning to assist in solving the 3-D motion planning problem of steering an AUV between two selected locations. We present simulation results for tracking a fresh water plume by use of our algorithm. Additionally, we present experimental results from field trials that test the skill of the model used as well as the incorporation of the model predictions into an AUV trajectory planner. These results indicate a modest, but measurable, improvement in surfacing error when the model predictions are incorporated into the planner.

This work addresses mission planning for autonomous underwater gliders based on predictions of an uncertain, time-varying current field. Glider submersibles are highly sensitive to prevailing currents so mission planners must account for ocean tides and eddies. Previous work in variable-current path planning assumes that current predictions are perfect, but in practice these forecasts may be inaccurate. Here we evaluate plan fragility using empirical tests on historical ocean forecasts for which followup data is available. We present methods for glider path planning and control in a time-varying current field. A case study scenario in the Southern California Bight uses current predictions drawn from the Regional Ocean Monitoring System (ROMS).

The value of Global Positioning Satellites (GPS) measurements to atmospheric science, space physics, and ocean science, is now emerging or showing a potential to play a major role in the evolving programs of NASA, NSF and NOAA. The objective of this communication is to identify and articulate the key scientific questions that are optimally, or perhaps uniquely, addressed by GPS or GPS-like observations, and discuss their relevance to existing or planned national Earth-science research programs. The GPS-based ocean reflection experiments performed to date have demonstrated the precision and spatial resolution suitable to altimetric applications that require higher spatial resolution and more frequent repeat than the current radar altimeter satellites. GPS radio occultation is promising as a climate monitoring tool because of its benchmark properties: its raw observable is based on extremely accurate timing measurements. GPS-derived temperature profiles can provide meaningful climate trend information over decadal time scales without the need for overlapping missions or mission-to-mission calibrations. By acquiring data as GPS satellites occult behind the Earth's limb, GPS also provides high vertical resolution information on the vertical structure of electron density with global coverage. New experimental techniques will create more comprehensive TEC maps by using signals reflected from the oceans and received in orbit. This communication will discuss a potential future GNSS Earth Observing System project which would deploy a constellation of satellites using GPS and GPS-like measurements, to obtain a) topography measurements based on GPS reflections with an accuracy and horizontal resolution suitable for eddy monitoring, and h) climate-records quality atmospheric temperature profiles. The constellation would also provide for measurements of ionospheric elec tron density. This is a good example of an interdisciplinary mission concept, with broad science objectives of high societal relevance, al l resting on common cost-effective technology.

Ocean salinity measurements using the Passive Active L/S-band instrument flying on the NCAR C-130 aircraft were made in July 2002 near Monterey, CA. When the radiometer data were corrected for the SST using the Klein and Swift salinity model and surface roughness effects using the L-band scatterometer, the retrieved salinity measurements had an RMS difference of 0.2-0.3 psu when compared with the R/V Point Sur ship measured salinity data.

Global climate modeling is one of the grand challenges of computational science, and ocean modeling plays an important role in both understanding the current climatic conditions and predicting the future climate change. Three-dimensional time-dependent ocean general circulation models (OGCMs) require a large amount of memory and processing time to run realistic simulations. Recent advances in computing hardware have dramatically affected the prospect of studying the global climate. The significant computational resources of massively parallel supercomputers promise to make such studies feasible. In addition to using advanced hardware, designing and implementing a well-optimized parallel ocean code will significantly improve the computational performance and reduce the total research time to complete these studies.In our present work, we chose the most widely used OGCM code as our base code. This OGCM is based on the Parallel Ocean Program (POP) developed in FORTRAN 90 on the Los Alamos CM-2 Connection Machine by the Los Alamos ocean modeling research group. During the first half of 1994, the code was ported to the Cray T3D by Cray Research using SHMEM-based message passing. Since the code on the T3D was still time-consuming when large problems were encountered, improving the code performance was considered essential.We have developed several general strategies to optimize the ocean general circulation model on the Cray T3D. These strategies include memory optimization, effective use of arithmetic pipelines, and usage of optimized libraries. The optimized code runs 2 to 2.5 times faster than the original code, which gives significant performance improvements for modeling large scaled ocean flows. Many test runs for both of the original and the optimized code have been carried out on the Cray T3D using various numbers of processors (1-256). Comparisons are made for a variety of real-world problems. A nearly linear scaling performance line is obtained for the optimized code, while the speed up data of the optimized code also shows excellent improvement over the original code.In addition to discussing the optimization of the code, we also address the issue of portability. Given the short life cycle of the massively parallel computer, usually on the order of three to five years, we emphasize the portability of the ocean model and the associated optimization routines across several computing platforms. Currently, the ocean modeling code has been ported successfully to the Hewlett Packard (HP)/Convex SPP-2000, and is readily portable to Cray T3E.This paper reports our efforts to optimize the parallel implementations of the oceanic model. So far, the work has focused on improving the load balancing and single node performance of the code on the Cray T3D. As a result, the atmosphere and ocean model components running side-by-side can achieve a performance level of slightly more than 10 GFLOPS on 512 processors of that machine. We have also developed a user-friendly coupling interface with atmospheric and biogeochemical models, in order to make the global climate modeling more complete and more realistic.