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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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Zepei Wu, Shuo Liu, Delong Zhao, Ling Yang, Zixin Xu, Zhipeng Yang, Dantong Liu, Tao Liu, Yan Ding, Wei Zhou, Hui He, Mengyu Huang, Ruijie Li, and Deping Ding

Abstract

Cloud particles have different shapes in the atmosphere. Research on cloud particle shapes plays an important role in analyzing the growth of ice crystals and the cloud microphysics. To achieve an accurate and efficient classification algorithm on ice crystal images, this study uses image-based morphological processing and principal component analysis, to extract features of images and apply intelligent classification algorithms for the Cloud Particle Imager (CPI). Currently, there are mainly two types of ice-crystal classification methods: one is the mode parameterization scheme, and the other is the artificial intelligence model. Combined with data feature extraction, the dataset was tested on ten types of classifiers, and the highest average accuracy was 99.07%. The fastest processing speed of the real-time data processing test was 2,000 images/s. In actual application, the algorithm should consider the processing speed, because the images are in the order of millions. Therefore, a support vector machine (SVM) classifier was used in this study. The SVM-based optimization algorithm can classify ice crystals into nine classes with an average accuracy of 95%, blurred frame accuracy of 100%, with a processing speed of 2,000 images/s. This method has a relatively high accuracy and faster classification processing speed than the classic neural network model. The new method could be also applied in physical parameter analysis of cloud microphysics.

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Seth F. Zippel, J. Thomas Farrar, Christopher J. Zappa, Una Miller, Louis St. Laurent, Takashi Ijichi, Robert A. Weller, Leah McRaven, Sven Nylund, and Deborah Le Bel

Abstract

Upper-ocean turbulence is central to the exchanges of heat, momentum, and gasses across the air/sea interface, and therefore plays a large role in weather and climate. Current understanding of upper-ocean mixing is lacking, often leading models to misrepresent mixed-layer depths and sea surface temperature. In part, progress has been limited due to the difficulty of measuring turbulence from fixed moorings which can simultaneously measure surface fluxes and upper-ocean stratification over long time periods. Here we introduce a direct wavenumber method for measuring Turbulent Kinetic Energy (TKE) dissipation rates, ϵ, from long-enduring moorings using pulse-coherent ADCPs. We discuss optimal programming of the ADCPs, a robust mechanical design for use on a mooring to maximize data return, and data processing techniques including phase-ambiguity unwrapping, spectral analysis, and a correction for instrument response. The method was used in the Salinity Processes Upper-ocean Regional Study (SPURS) to collect two year-long data sets. We find the mooring-derived TKE dissipation rates compare favorably to estimates made nearby from a microstructure shear probe mounted to a glider during its two separate two-week missions for O (10−8) ≤ ϵO (10−5) m2 s−3. Periods of disagreement between turbulence estimates from the two platforms coincide with differences in vertical temperature profiles, which may indicate that barrier layers can substantially modulate upper-ocean turbulence over horizontal scales of 1-10 km. We also find that dissipation estimates from two different moorings at 12.5 m, and at 7 m are in agreement with the surface buoyancy flux during periods of strong nighttime convection, consistent with classic boundary layer theory.

Open access
Joaquin Cuomo and V. Chandrasekar

Abstract

Nowcasting based on weather radar uses the current and past observations to make estimations of future radar echoes. There are many types of operationally deployed nowcasting systems, but none of them are currently based on deep learning, despite it being an active area of research in the last few years. This paper explores deep learning models as alternatives to current methods by proposing different architectures and comparing them against some operational nowcasting systems. The methods proposed here, harnessing residual convolutional encoder-decoder architectures, reach a level of performance expected of current systems and in certain scenarios can even outperform them. Finally, some of the potential drawbacks of using deep learning are analyzed. No decay in the performance on a different geographical area from where the models were trained was found. No edge or checkerboard artifact, common in convolutional operations, was found that affects the nowcasting metrics.

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Armand Neukermans, Gary Cooper, Jack Foster, Lee Galbraith, and Sudhanshu Jain

Abstract

Two methods for the laboratory-scale formation of aerosols of nanosized particles of precipitated calcium carbonate (PCC), for potential use in Stratospheric Aerosol Injection (SAI), a Solar Radiation Management (SRM) technique, are described. The first uses the coarse fluidization of bulk PCC in a simple vessel, followed by dispersal using a commercially available two-fluid nozzle. The manufacturer’s measured particle mass distribution for the bulk material, and sprayed aerosol particle mass distributions are compared, indicating that the sprayed particles are well separated in spite of a notoriously problematic agglomeration tendency. The method is suitable for scale-up. A second dispersal method, useful for small laboratory experiments, using liquid carbon dioxide as a dispersant as well as spray propellant gave similar results. The mass mode diameters measured here (0.89 to 1.4 μm) differ from that stated by the manufacturer (0.7 μm), but the distributions are consistent in showing complete separation of the particles.

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Junhong Wang, Jerry Brotzge, Jacob Shultis, and Nathan Bain

Abstract

The accurate detection and monitoring of freezing rain and icing conditions at the surface is a notoriously challenging but important problem. This work attempts to enhance icing detection and characterization utilizing data from the New York State Mesonet (NYSM). NYSM is the first operational network measuring winds at 10 meters from two independent sensors: propeller and sonic anemometers. During and after freezing rain events, large wind speed differences are frequently reported between the two anemometers because the propeller develops a coating of ice, thus either stopping or slowing its rotation. Such errors of propeller data provide a signal for identifying icing conditions. An automated method for identifying “active freezing rain” (AFR) and a continuation of “frozen surface” (FS) conditions is developed. Hourly maps of AFR and FS sites are generated using four criteria: (1) a wind speed difference (sonic – propeller) of > 1 m s-1 or 0 m s-1 propeller wind speed for at least half hour, (2) a temperature threshold of -5°C to 2°C for AFR and less than 2°C for FS, (3) insignificant hourly snow accumulation, and (4) with (or without) significant hourly precipitation accumulation for AFR (or FS). The AFR events detected by the automated method for last four winters (2017-2021) show very good agreements in starting and ending times with that from ASOS data. A case study of the ice storm during 14-16 April 2018 further demonstrates the validity of the methodology and highlights the benefit of NYSM profiler and camera data.

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A.V Kochin, F.A Zagumennov, and V.L Fomenko

Abstract

Improving the quality of weather forecasts and the reliability of climate research requires increasing the reliability of measurements. This paper presents results for optical sensors attached to radiosondes. These sensors can measure cloud-top height (CTH) with high accuracy, determine the presence of precipitation particles in clouds and the height of the boundary between the tropospheric and stratospheric air masses. These research findings are especially important in the Arctic, where the reliability of cloud data is poor, especially during polar nights. With the help of a visible range optical sensor, during the daytime, it is possible to measure CTH with an accuracy of 50 meters. Using data from an IR sensor it is possible to measure CTH both day and night. The paper also discusses the possibility of using optical sensors in an observational network. The results from this study could be useful for both weather forecasting and climate research.

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Cesar M. Salazar Aquino, Boonleng Cheong, and Robert D. Palmer

Abstract

In this paper, a novel technique is proposed to mitigate the so-called blind range on radars that use pulse compression. It is well known that the blind range is caused by the strong leak-through into the receiver during the transmission cycle. The proposed technique is called progressive pulse compression (PPC) and is based on partial decoding. PPC uses a portion of the uncontaminated received signal in conjunction with pulse compression to estimate the echoes from the incomplete signal. The technique does not require the use of a fill pulse or any hardware modifications. PPC can be divided into three steps. The fist step is to discard all the received signals during the transmit cycle and apply a smooth taper for continuous transition from zero to one. The second step is to perform the pulse compression using matched filter. The combination of these two steps is equivalent to performing pulse compression using a progressively changing template to partially extract the uncontaminated received signal for compression. The third step is to compensate for the progressively changing template so that proper reflectivity values can be recovered. This technique has been tested on the PX-1000 and will be implemented on PX-10k in the near future. These two radars are designed and operated by the Advanced Radar Research Center at the University of Oklahoma and are both X-band software-defined solid-state systems. The results presented in this paper are collected using the PX-1000 radar.

Open access
Sean M. Waugh

Abstract

Obtaining quality air temperature measurements in complex mesoscale environments, such as thunderstorms or frontal zones, is problematic, and particularly challenging from a moving platform. For some time mobile weather platforms known as Mobile Mesonets (MMs) have used custom aspirated temperature shields. The original design was known as the “J-Tube”, which addresses some but not all of the unique problems associated with mobile temperature measurements. For VORTEX-2 2009, a second, well documented shield, the R.M. Young (RMY) 43408 was included but was also found to have certain shortcomings in some severe weather environments. Between the end of VORTEX2 2009 and the start of VORTEX2 2010, a third and new shield called the “U-tube” was designed, tested and installed.

Reported here are the results of efforts to better characterize the J-Tube, RMY 43408, and the U-Tube. Several tests designed to isolate key aspects of a radiation shield’s performance, such as performance in rain, high solar radiation, varying wind conditions, and general response time were completed. A period of intercomparison between the three shields during the 2010 season of VORTEX 2 is also used to highlight each shield being used in “real world” conditions. Results indicate that the U-Tube has several significant advantages over the J-tube and 43408 in terms of aspiration rate, sampling efficiency, performance during rain, variable winds, and high solar radiation periods, as well as response time. Given these results, the U-tube should be utilized for mobile observations going forward.

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