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1. Transmitted Cross-Polarized Light Detection of Particulate Inorganic Carbon Concentrations and Fluxes in the Ocean Water Column: Ships to ARGO Floats

   https://doi.org/10.3389/frsen.2022.837938  

   Bishop, James K. ; Amaral, Vinicius J. ; Lam, Phoebe J. ; Wood, Todd J. ; Lee, Jong-Mi ; Laubach, Allison ; Barnard, Andrew ; Derr, Alex ; Orrico, Cristina ( March 2022 , Frontiers in Remote Sensing)

   Particulate inorganic carbon (PIC) plays a major role in the ocean carbon cycle impacting pH, dissolved inorganic carbon, and alkalinity, as well as particulate organic carbon (POC) export and transfer efficiency to the deep sea. Remote sensing retrievals of PIC in surface waters span two decades, yet knowledge of PIC concentration variability in the water column is temporally and spatially limited due to a reliance on ship sampling. To overcome the space–time gap in observations, we have developed optical sensors for PIC concentration and flux that exploit the high mineral birefringence of CaCO 3 minerals, and thus enable real-time datamore »when deployed operationally from ship CTDs and ARGO-style Carbon Flux Explorer floats. For PIC concentrations, we describe a fast (10 Hz) digital low-power (∼0.5 W) sensor that utilizes cross-polarized transmitted light to detect the photon yield from suspended birefringent particles in the water column. This sensor has been CTD-deployed to depths as great as 6,000 m and cross-calibrated against particulates sampled by large volume in situ filtration and CTD/rosettes. We report data from the September–November 2018 GEOTRACES GP15 meridional transect from the Aleutian Islands to Tahiti along 152°W where we validated two prototype sensors deployed on separate CTD systems surface to bottom at 39 stations, many of which were taken in nearly particle-free waters. We compare sensor results with major particle phase composition (particularly PIC and particulate aluminum) from simultaneously collected size-fractionated particulate samples collected by large volume in situ filtration. We also report results from the June 2017 California Current Ecosystem-Long Term Ecological Research (CCE-LTER) process study in California coastal waters where high PIC levels were found. We demonstrate that the PIC concentration sensor can detect PIC concentration variability from 0.01 to >1 μM in the water column (except in nepheloid layers) and outline engineering needs and progress on its integration with the Carbon Flux Explorer, an autonomous float.« less
2. Collaborative Sampling Using Heterogeneous Marine Robots Driven by Visual Cues

   https://doi.org/10.1109/CRV.2017.49  

   Manjanna, Sandeep ; Hansen, Johanna ; Li, Alberto Quattrini ; Rekleitis, Ioannis ; Dudek, Gregory ( May 2017 , Conference on Computer and Robot Vision (CRV))

   This paper addresses distributed data sampling in marine environments using robotic devices. We present a method to strategically sample locally observable features using two classes of sensor platforms. Our system consists of a sophisticated autonomous surface vehicle (ASV) which strategically samples based on information provided by a team of inexpensive sensor nodes. The sensor nodes effectively extend the observational capabilities of the vehicle by capturing georeferenced samples from disparate and moving points across the region. The ASV uses this information, along with its own observations, to plan a path so as to sample points which it expects to be particularlymore »informative. We compare our approach to a traditional exhaustive survey approach and show that we are able to effectively represent a region with less energy expenditure. We validate our approach through simulations and test the system on real robots in field.« less
3. Dynamic Autonomous Surface Vehicle Controls Under Changing Environmental Forces

   Jason Moulton, Nare Karapetyan ( July 2019 , 12th Conference on Field and Service Robotics (FSR))

   The ability to navigate, search, and monitor dynamic marine environments such as ports, deltas, tributaries, and rivers presents several challenges to both human operated and autonomously operated surface vehicles. Human data collection and monitoring is overly taxing and inconsistent when faced with large coverage areas, disturbed environments, and potentially uninhabitable situations. In contrast, the same missions become achievable with autonomous surface vehicles (ASV) configured and capable of accurately maneuvering in such environments. The two dynamic factors that present formidable challenges to completing precise maneuvers in coastal and moving waters are currents and winds. In this work, we present novel andmore »inexpensive methods for sensing these external forces, together with methods for accurately controlling an ASV in the presence of such external forces. The resulting platform is capable of deploying bathymetric and water quality monitoring sensors. Experimental results in the local lakes and rivers demonstrate the feasibility of the proposed approach.« less
4. A system of coordinated autonomous robots for Lagrangian studies of microbes in the oceanic deep chlorophyll maximum

   https://doi.org/10.1126/scirobotics.abb9138  

   Zhang, Yanwu ; Ryan, John P. ; Hobson, Brett W. ; Kieft, Brian ; Romano, Anna ; Barone, Benedetto ; Preston, Christina M. ; Roman, Brent ; Raanan, Ben-Yair ; Pargett, Douglas ; et al ( January 2021 , Science Robotics)

   The deep chlorophyll maximum (DCM) layer is an ecologically important feature of the open ocean. The DCM cannot be observed using aerial or satellite remote sensing; thus, in situ observations are essential. Further, understanding the responses of microbes to the environmental processes driving their metabolism and interactions requires observing in a reference frame that moves with a plankton population drifting in ocean currents, i.e., Lagrangian. Here, we report the development and application of a system of coordinated robots for studying planktonic biological communities drifting within the ocean. The presented Lagrangian system uses three coordinated autonomous robotic platforms. The focal platformmore »consists of an autonomous underwater vehicle (AUV) fitted with a robotic water sampler. This platform localizes and drifts within a DCM community, periodically acquiring samples while continuously monitoring the local environment. The second platform is an AUV equipped with environmental sensing and acoustic tracking capabilities. This platform characterizes environmental conditions by tracking the focal platform and vertically profiling in its vicinity. The third platform is an autonomous surface vehicle equipped with satellite communications and subsea acoustic tracking capabilities. While also acoustically tracking the focal platform, this vehicle serves as a communication relay that connects the subsea robot to human operators, thereby providing situational awareness and enabling intervention if needed. Deployed in the North Pacific Ocean within the core of a cyclonic eddy, this coordinated system autonomously captured fundamental characteristics of the in situ DCM microbial community in a manner not possible previously.

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5. The Reprocessed Suomi NPP Satellite Observations

   https://doi.org/10.3390/rs12182891  

   Zou, Cheng-Zhi ; Zhou, Lihang ; Lin, Lin ; Sun, Ninghai ; Chen, Yong ; Flynn, Lawrence E. ; Zhang, Bin ; Cao, Changyong ; Iturbide-Sanchez, Flavio ; Beck, Trevor ; et al ( September 2020 , Remote Sensing)

   The launch of the National Oceanic and Atmospheric Administration (NOAA)/ National Aeronautics and Space Administration (NASA) Suomi National Polar-orbiting Partnership (S-NPP) and its follow-on NOAA Joint Polar Satellite Systems (JPSS) satellites marks the beginning of a new era of operational satellite observations of the Earth and atmosphere for environmental applications with high spatial resolution and sampling rate. The S-NPP and JPSS are equipped with five instruments, each with advanced design in Earth sampling, including the Advanced Technology Microwave Sounder (ATMS), the Cross-track Infrared Sounder (CrIS), the Ozone Mapping and Profiler Suite (OMPS), the Visible Infrared Imaging Radiometer Suite (VIIRS), andmore »the Clouds and the Earth’s Radiant Energy System (CERES). Among them, the ATMS is the new generation of microwave sounder measuring temperature profiles from the surface to the upper stratosphere and moisture profiles from the surface to the upper troposphere, while CrIS is the first of a series of advanced operational hyperspectral sounders providing more accurate atmospheric and moisture sounding observations with higher vertical resolution for weather and climate applications. The OMPS instrument measures solar backscattered ultraviolet to provide information on the concentrations of ozone in the Earth’s atmosphere, and VIIRS provides global observations of a variety of essential environmental variables over the land, atmosphere, cryosphere, and ocean with visible and infrared imagery. The CERES instrument measures the solar energy reflected by the Earth, the longwave radiative emission from the Earth, and the role of cloud processes in the Earth’s energy balance. Presently, observations from several instruments on S-NPP and JPSS-1 (re-named NOAA-20 after launch) provide near real-time monitoring of the environmental changes and improve weather forecasting by assimilation into numerical weather prediction models. Envisioning the need for consistencies in satellite retrievals, improving climate reanalyses, development of climate data records, and improving numerical weather forecasting, the NOAA/Center for Satellite Applications and Research (STAR) has been reprocessing the S-NPP observations for ATMS, CrIS, OMPS, and VIIRS through their life cycle. This article provides a summary of the instrument observing principles, data characteristics, reprocessing approaches, calibration algorithms, and validation results of the reprocessed sensor data records. The reprocessing generated consistent Level-1 sensor data records using unified and consistent calibration algorithms for each instrument that removed artificial jumps in data owing to operational changes, instrument anomalies, contaminations by anomaly views of the environment or spacecraft, and other causes. The reprocessed sensor data records were compared with and validated against other observations for a consistency check whenever such data were available. The reprocessed data will be archived in the NOAA data center with the same format as the operational data and technical support for data requests. Such a reprocessing is expected to improve the efficiency of the use of the S-NPP and JPSS satellite data and the accuracy of the observed essential environmental variables through either consistent satellite retrievals or use of the reprocessed data in numerical data assimilations.« less