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Travis Miles, Wayne Slade, and Scott Glenn

Abstract

Suspended particle size and concentration are critical parameters that are necessary to understand water quality, sediment dynamics, carbon flux, and ecosystem dynamics, among other ocean processes. In this study we detail the integration of a Sequoia Scientific, Inc., Laser In Situ Scattering and Transmissometry (LISST) sensor into a Teledyne Webb Research Slocum autonomous underwater glider. These sensors are capable of measuring particle size, concentration, and beam attenuation by particles in size ranges from 1.00 to 500 μm at a resolution of 1 Hz. The combination of these two technologies provides the unique opportunity to measure particle characteristics persistently at specific locations or to survey regional domains from a single profiling sensor. In this study we present the sensor integration framework, detail quality assurance and control procedures, and provide a case study of storm-driven sediment resuspension and transport. Specifically, Rutgers glider RU28 was deployed with an integrated LISST-Glider for 18 days in September of 2017. During this period, it sampled the nearshore environment off coastal New Jersey, capturing full water column sediment resuspension during a coastal storm event. A novel method for in situ background corrections is demonstrated and used to mitigate long-term biofouling of the sensor windows. In addition, we present a method for removing schlieren-contaminated time periods utilizing coincident conductivity temperature and depth, fluorometer, and optical backscatter data. The combination of LISST sensors and autonomous platforms has the potential to revolutionize our ability to capture suspended particle characteristics throughout the world’s oceans.

Open access
Julien Marty, Benoit Doury, and Alfred Kramer

Abstract

This paper presents new low and high power spectral density models for pressure fluctuations at the Earth’s surface over the frequency range of (10−5 – 8) Hz. Previously proposed models often included limitations, such as a much narrower frequency range, the inclusion of erroneous and non-calibrated data or recorded data not deconvolved from the measurement system responses. The progress recently made with response modeling and field calibration of pressure fluctuation measurement systems now allows to propose more realistic power spectral density models over an extremely large frequency band. This paper describes how the data were selected, processed, and analyzed to obtain the final global models. In addition, the intermediate results allow the characterization of several atmospheric mechanisms, such as gravity wave saturation, limits of the buoyancy and acoustic cut-off frequencies or wind turbulence modes. The two proposed low and high power spectral density models are planned to be used for a wide range of applications, including assessing the quality of measured pressure fluctuations, verifying the validity of modeled pressure fluctuations and supporting the design, testing and calibration of a new generation of measurement systems. The models presented in this paper are made available to the scientific community.

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Mampi Sarkar, Paquita Zuidema, and Virendra Ghate

Abstract

Precipitation is a key process within the shallow cloud lifecycle. The Cloud System Evolution in the Trades (CSET) campaign included the first deployment of a 94 GHz Doppler radar and 532 nm lidar. Despite a larger sampling volume, initial mean radar/lidar retrieved rain rates (Schwartz et al. 2019) based on the upward-pointing remote sensor datasets are systematically less than those measured by in-situ precipitation probes in the cumulus regime. Subsequent retrieval improvements produce rainrates that compare better to in-situ values, but still underestimate. Retrieved shallow cumulus drop sizes can remain too small and too few, with an overestimated shape parameter narrowing the raindrop size distribution too much. Three potential causes for the discrepancy are explored: the gamma functional fit to the dropsize distribution, attenuation by rain and cloud water, and an underaccounting of Mie dampening of the reflectivity. A truncated exponential fit may represent the dropsizes below a showering cumulus cloud more realistically, although further work would be needed to fully evaluate the impact of a different dropsize representation upon the retrieval. The rain attenuation is within the measurement uncertainty of the radar. Mie dampening of the reflectivity is shown to be significant, in contrast to previous stratocumulus campaigns with lighter rain rates, and may be difficult to constrain well with the remote measurements. An alternative approach combines an a priori determination of the dropsize distribution width based on the in-situ data with the mean radar Doppler velocity and reflectivity. This can produce realistic retrievals, although a more comprehensive assessment is needed to better characterize the retrieval errors.

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Shudong He, Youduo Peng, Yongping Jin, Jian Yan, and Buyan Wan

Abstract

Deep-sea sediments hold evolutionary records of the oceanic environment, records of great significance for scientific fields investigating marine sedimentary processes, structural evolution, and seabed mineral resource exploration. However, the acquisition of original samples from deep-sea sediments is completely dependent on advanced seabed sediment collection methods and technical equipment. In this paper, a novel sampler is proposed to obtain intact sediment samples at full-ocean-depth. It mainly consists of a sampling device, pressure-retaining device, pressure-compensating device and sample transfer device. The sampler can collect samples at full-ocean-depth (11,000 m) with a maximum core diameter of 54 mm and core length of 350 mm, and samples can be maintained at near in situ pressures during recovery. The sampler can be installed on a remote operated vehicle (ROV) or human occupied vehicle (HOV), and operated with a single mechanical arm to collect pressure-retained samples. The experimental test showed that the novel sampler had good pressure-retaining performance and suitability with a mechanical arm, and can be applied to pressure-retaining sampling of seabed sediments at depth of 11,000 m.

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Zaid R. Al-Attabi, George Voulgaris, and Daniel C. Conley

Abstract

An examination of the applicability and accuracy of the empirical wave inversion method in the presence of swell waves is presented. The ability of the method to invert Doppler spectra to wave directional spectra and bulk wave parameters is investigated using one-month data from a 12 MHz WERA High Frequency (HF) radar system and in-situ data from a wave buoy. Three different swell inversion models are evaluated: LPM (Lipa et al. 1981), WFG (Wang et al. 2016) and EMP, an empirical approach introduced in this study. The swell inversions were carried out using two different scenarios: (1) a single beam from a single radar site and two beams from a single radar site, and (2) two beams from two sites (a single beam per site) intersecting each other at the buoy location. The LPM method utilized using two beams from two different sites was found to provide the best estimations of swell parameters (swell height RMS error 0.24m) and showed a good correlation with the partitioned swell in-situ values. For the wind wave inversion, the empirical method presented here is used with an empirical coefficient of 0.3 which seems to be suitable for universal application for all radar operating frequencies. The inverted swell parameters are used to create a swell spectrum which is combined with the inverted wind wave spectrum to create a full directional wave spectrum. The wave inversion method presented in this study although empirical does not require calibration with in situ data and can be applied to any beam forming system and operating frequency.

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Ryan Lagerquist, David Turner, Imme Ebert-Uphoff, Jebb Stewart, and Venita Hagerty

Abstract

This paper describes the development of U-net++ models, a type of neural network that performs deep learning, to emulate the shortwave Rapid Radiative-transfer Model (RRTM). The goal is to emulate the RRTM accurately in a small fraction of the computing time, creating a U-net++ that could be used as a parameterization in numerical weather prediction (NWP). Target variables are surface downwelling flux, top-of-atmosphere upwelling flux (FupTOA), net flux, and a profile of radiative-heating rates. We have devised several ways to make the U-net++ models knowledge-guided, recently identified as a key priority in machine learning (ML) applications to the geosciences. We conduct two experiments to find the best U-net++ configurations. In Experiment 1, we train on non-tropical sites and test on tropical sites, to assess extreme spatial generalization. In Experiment 2, we train on sites from all regions and test on different sites from all regions, with the goal of creating the best possible model for use in NWP. The selected model from Experiment 1 shows impressive skill on the tropical testing sites, except four notable deficiencies: large bias and error for heating rate in the upper stratosphere, unreliable FupTOA for profiles with single-layer liquid cloud, large heating-rate bias in the mid-troposphere for profiles with multi-layer liquid cloud, and negative bias at lowzenith angles for all flux components and tropospheric heating rates. The selected model from Experiment 2 corrects all but the first deficiency, and both models run ~104 times faster than the RRTM. Our code is available publicly.

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Mark Curtis, Sandy Dance, Valentin Louf, and Alain Protat

Abstract

For mechanically scanning weather radars, precise pointing of the antenna is a key factor in ensuring accurate observation of the atmosphere at far range. Since operational radars typically scan the atmosphere using a series of 360° sweeps at fixed elevation angles, level scanning during azimuthal rotation is also important, but often not actively monitored after installation.

One method of gauging pointing accuracy of a radar is to use solar interference which occurs as the antenna sweeps past the sun. By comparing the observed position of the sun with its known position, an estimate of pointing error in both elevation and azimuth can be obtained. A basic model for this error assumes that the radar sweep is perfectly level and that biases in elevation are therefore independent of azimuth. We extend this model to allow for the possibility that the plane of rotation may not be level. Consequently, the direction and severity of tilt may be diagnosed in addition to any constant error in elevation and azimuth pointing.

The extended model was applied to a subset of radars from the Australian weather radar network resulting in the discovery of several out of level radars. One radar, Captains Flat near Canberra, showed a severe tilt of 0.81° prompting inspection by a technician. This revealed that mounting studs on the pedestal of the radar tower were badly worn and loose. Correction of this issue resolved the tilt component of the diagnosed elevation error and prevented further mechanical damage to the instrument.

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F. Joseph Turk, Ramon Padullés, Estel Cardellach, Chi O. Ao, Kuo-Nung Wang, David D. Morabito, Manuel de la Torre Juarez, Mayra Oyola, Svetla Hristova-Veleva, and J. David Neelin

Abstract

Observationally, a major source of uncertainty in evaluation of climate models arises from the difficulty in obtaining globally distributed, fine scale profiles of temperature, pressure and water vapor, that probe through convective precipitating clouds, from the boundary layer to the upper levels of the free troposphere. In this manuscript, a two-year analysis of data from the Radio Occultations through Heavy Precipitation (ROHP) polarimetric RO demonstration mission onboard the Spanish PAZ spacecraft is presented. ROHP measures the difference in the differential propagation phase delay (Δ𝜙) between two orthogonal polarization receive states that is induced from the presence of non-spherically shaped hydrometeors along the Global Navigation Satellite System (GNSS) propagation path, complementing the standard RO thermodynamic profile. Since Δφ is a net path-accumulated depolarization and does not resolve the precipitation structure along the propagation path, orbital coincidences between ROHP and the Global Precipitation Measurement (GPM) constellation passive MW radiometers are identified to provides three-dimensional precipitation context to the RO thermodynamic profile. Passive MW-derived precipitation profiles are used to simulate the Δφ along the ROHP propagation paths. Comparison between the simulated and observed Δφ are indicative of the ability of ROHP to detect threshold levels of ray path-averaged condensed water content, as well as to suggest possible inferences on the average ice phase hydrometeor non-sphericity. The use of the polarimetric RO vertical structure is demonstrated as a means to condition the lower tropospheric humidity by the top-most height of the associated convective cloud structure.

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Ali Tokay, Annakaisa von Lerber, Claire Pettersen, Mark S. Kulie, Dmitri N. Moisseev, and David B. Wolff

Abstract

Performance of the Precipitation Imaging Package (PIP) for estimating the snow water equivalent (SWE) is evaluated through a comparative study with the collocated National Oceanic and Atmospheric Administration National Weather Service snow stake field measurements. The PIP together with a vertically pointing radar, a weighing bucket gauge, and a laser-optical disdrometer was deployed at the NWS Marquette, Michigan office building for a long-term field study supported by the National Aeronautics and Space Administration’s Global Precipitation Measurement mission Ground Validation program. The site was also equipped with a weather station. During the 2017-18 winter, the PIP functioned nearly uninterrupted at frigid temperatures accumulating 2345.8 mm of geometric snow depth over a total of 499 hours. This long record consists of 30 events, and the PIP-retrieved and snow stake field measured SWE differed less than 15% in every event. Two of the major events with the longest duration and the highest accumulation are examined in detail. The particle mass with a given diameter was much lower during a shallow, colder, uniform lake-effect event than in the deep, less cold, and variable synoptic event. This study demonstrated that the PIP is a robust instrument for operational use, and is reliable for deriving the bulk properties of falling snow.

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Hans van Haren, Roel Bakker, Yvo Witte, Martin Laan, and Johan van Heerwaarden

Abstract

The redistribution of matter in the deep-sea depends on water-flow currents and turbulent exchange, for which breaking internal waves are an important source. As internal waves and turbulence are essentially three-dimensional ‘3D’, their dynamical development should ideally be studied in a volume of seawater. However, this is seldom done in the ocean where 1D-observations along a single vertical line are already difficult. We present the design, construction and successful deployment of a half-cubic-hectometer (480,000 m3) 3D-T mooring array holding 2925 high-resolution temperature sensors to study weakly density-stratified waters of the 2500-m deep Western Mediterranean. The stand-alone array samples temperature at a rate of 0.5 Hz, with precision <0.5 mK, noise level <0.1 mK and expected endurance of 3 years. The independent sensors are synchronized inductively every 4 h to a single standard clock. The array consists of 45 vertical lines 125 m long, at 9.5 m horizontally from their nearest neighbor. Each line is held under tension of 1.3 kN by a buoyancy element that is released chemically one week after deployment. All fold-up lines are attached to a grid of cables that is tensioned in a 70 m diameter ring of steel tubes. The array is build-up in harbor-waters, with air filling the steel tubes for floatation. The flat-form array is towed to the mooring site under favorable sea-state conditions. By opening valves in the steel tubes, the array is sunk and its free-fall is controlled by a custom-made drag-parachute reducing the average sinking speed to 1.3 m s-1 and providing smooth horizontal landing on the flat seafloor.

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