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Felix Erdmann, Olivier Caumont, and Eric Defer

Abstract

Coincident Geostationary Lightning Mapper (GLM) and National Lightning Detection Network (NLDN) observations are used to build a generator of realistic lightning optical signal in the perspective to simulate Lightning Imager (LI) signal from European NLDN-like observations. Characteristics of GLM and NLDN flashes are used to train different machine-learning (ML) models, which predict simulated pseudo-GLM flash extent, flash duration, and event number per flash (targets) from several NLDN flash characteristics. Comparing statistics of observed GLM targets and simulated pseudo-GLM targets, the most suitable ML-based target generators are identified. The simulated targets are then further processed to obtain pseudo-GLM events and flash-scale products. In the perspective of lightning data assimilation, flash extent density (FED) is derived from both observed and simulated GLM data. The best generators simulate accumulated hourly FED sums with a bias of 2% to the observation while cumulated absolute differences remain of about 22%. A visual comparison reveals that hourly simulated FED features local maxima at the similar geolocations as the FED derived from GLM observations. However, the simulated FED often exceeds the observed FED in regions of convective cores and high flash rates. The accumulated hourly area with FED > 0 flashes per 5 km × 5 km pixel simulated by some pseudo-GLM generators differs by only 7%–8% from the observed values. The recommended generator uses a linear support vector regressor (linSVR) to create pseudo-GLM FED. It provides the best balance between target simulation, hourly FED sum, and hourly electrified area.

Open access
S. J. Lentz, A. Kirincich, and A. J. Plueddemann

Abstract

Acoustic Doppler current profilers (ADCP) do not provide reliable water velocity measurements near the sea surface or bottom because acoustic sidelobe reflections from the boundary contaminate the Doppler velocity measurements. The apparent depth of the center of the sidelobe reflection is z sl = ha[1 − cos(θ)], where ha is the distance from the ADCP acoustic head to the sea surface and θ is the ADCP beam angle. However, sidelobe contamination extends one and a half ADCP bins below z sl as the range gating of the acoustic return causes overlap between adjacent ADCP bins. Consequently, the contaminated region z < z sl + 3Δz/2 is deeper than traditionally suggested, with a dependence on bin size Δz. Direct observations confirming both the center depth of the sidelobe reflection and the depth of contamination are presented for six bottom-mounted, upward-looking ADCPs. The sidelobe reflection is isolated by considering periods of weak wind stresses when the sea surface is smooth and there is nearly perfect reflection of the main beams away from the ADCP and hence little acoustic return from the main beams to the ADCP.

Open access
David T. Walker and Kelsey Brunner

Abstract

This paper describes a variational data assimilation algorithm based on the Simulating WAves Nearshore (SWAN) wave spectrum model. The approach allows single-point wave spectrum observations to be used to estimate the wave field for a nearshore region under stationary conditions, assuming a spatially uniform incident wave spectrum at the offshore boundary. The assimilated data are in the form of Fourier directional coefficients, the standard output from operational wave buoys, and are used directly by incorporating the relationship between directional spectrum and the Fourier coefficients into the formulation. The algorithm was tested on data from nearshore buoys deployed off the coast of North Carolina in May 2012, and the estimated wave field is compared to both the input data and independent observation data. The results compare favorably to the independent data with overall RMS errors of 10%–20% for significant wave height, about half a second for mean wave period, and as much as three to four SWAN spectral grid cells for mean direction. Overall, the results show that the algorithm can be effectively used to estimate the offshore boundary spectrum and accurately reproduce wave conditions in the domain.

Open access
Lijuan Yang, Hanqiu Xu, and Shaode Yu

Abstract

The coarse Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) product (spatial resolution: 3 km) retrieved by the dark-target algorithm always generates the missing values when being adopted to estimate the ground-level PM2.5 concentrations. In this study, we developed a two-stage random forest using MODIS 3-km AOD to obtain the PM2.5 concentrations with full coverage in a contiguous coastal developed region, i.e., Yangtze River delta–Fujian–Pearl River delta (YRD–FJ–PRD) region of China. A first-stage random forest–integrated six meteorological fields was employed to predict the missing values of AOD product, and the combined AOD (i.e., random forest–derived AOD and MODIS 3-km AOD) incorporated with other ancillary variables were developed for predicting PM2.5 concentrations within a second-stage random forest model. The results showed that the first-stage random forest could explain 94% of the AOD variability over YRD–FJ–PRD region, and we achieved a site-based cross validation (CV) R 2 of 0.87 and a time-based CV R 2 of 0.85. The full-coverage PM2.5 concentrations illustrated a spatial pattern with annual-mean PM2.5 of 46, 40, and 35 μg m−3 in YRD, PRD, and FJ, respectively, sharing the same trend with previous studies. Our results indicated that the proposed two-stage random forest model could be effectively used for PM2.5 estimation in different areas.

Open access
Bofu Zheng, Andrew J. Lucas, Robert Pinkel, and Arnaud Le Boyer

Abstract

The Wirewalker (WW) ocean-wave-powered vertical profiling system allows the collection of high-resolution oceanographic data due to its rapid profiling, hydrodynamically quiet operation, and long endurance. We have assessed the potential for measuring fine-scale ocean velocities from the Wirewalker platform using commercially available acoustic velocimeters. Although the vertical profiling speed is relatively steady, platform motion affects the velocity measurements and requires correction. We present an algorithm to correct our velocity estimates using platform motion calculated from the inertial sensors – accelerometer, gyroscope, and magnetometer – on a Nortek Signature1000 Acoustic Doppler Current Profiler. This correction, carried out ping-by-ping, was effective in removing the vehicle motion from the measured velocities. The motion-corrected velocities contain contributions from surface wave orbital velocities, especially near the surface, and the background currents. To proceed, we use an averaging approach that leverages both the vertical platform profiling of the system and the ~15-20 m vertical profiling range resolution of the down-looking ADCP to separate the surface wave orbital velocities and the background flow. The former can provide information on the wave conditions. From the latter, we are able to estimate fine-scale velocity and shear with spectral wavenumber roll-off at vertical scales around 3 m, a vertical resolution several times finer than that possible from modern shipboard or fixed ADCPs with similar profiling range, and similar to recent glider measurements. When combined with a continuous time-series of buoy drift calculated from the onboard GPS, a highly-resolved total velocity field is obtained, with a unique combination of space and time resolution.

Open access
Christopher Daly, Matthew K. Doggett, Joseph I. Smith, Keith V. Olson, Michael D. Halbleib, Zlatko Dimcovic, Dylan Keon, Rebecca A. Loiselle, Ben Steinberg, Adam D. Ryan, Cherri M. Pancake, and Eileen M. Kaspar

Abstract

There is a great need for gridded daily precipitation datasets to support a wide variety of disciplines in science and industry. Production of such datasets faces many challenges, from station data ingest to gridded dataset distribution. The quality of the dataset is directly related to its information content, and each step in the production process provides an opportunity to maximize that content. The first opportunity is maximizing station density from a variety of sources and assuring high quality through intensive screening, including manual review. To accommodate varying data latency times, the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) Climate Group releases eight versions of a day’s precipitation grid, from 24 h after day’s end to 6 months of elapsed time. The second opportunity is to distribute the station data to a grid using methods that add information and minimize the smoothing effect of interpolation. We use two competing methods, one that utilizes the information in long-term precipitation climatologies, and the other using weather radar return patterns. Last, maintaining consistency among different time scales (monthly vs daily) affords the opportunity to exploit information available at each scale. Maintaining temporal consistency over longer time scales is at cross purposes with maximizing information content. We therefore produce two datasets, one that maximizes data sources and a second that includes only networks with long-term stations and no radar (a short-term data source). Further work is under way to improve station metadata, refine interpolation methods by producing climatologies targeted to specific storm conditions, and employ higher-resolution radar products.

Open access
Julia W. Fiedler, Lauren Kim, Robert L. Grenzeback, Adam P. Young, and Mark A. Merrifield

Abstract

We demonstrate that a hovering, drone-mounted laser scanner (lidar) paired with a survey-grade satellite and inertial positioning system measures the wave transformation across the surf zone and the resulting runup with accuracy almost equal to a stationary truck-mounted terrestrial lidar. The drone, a multirotor small uncrewed aircraft system (sUAS), provides unobstructed measurements by hovering above the surf zone at 20-m elevation while scanning surfaces along a 150-m-wide cross-shore transect. The drone enables rapid data collection in remote locations where terrestrial scanning may not be possible. Allowing for battery changes, about 17 min of scanning data can be acquired every 25 min for several hours. Observations were collected with a wide (H s = 2.2 m) and narrow (H s = 0.8 m) surf zone, and are validated with traditional land-based survey techniques and an array of buried pressure sensors. Thorough postprocessing yields a stable (σ¯=1.7cm) back beach topography estimate comparable to the terrestrial lidar (σ¯=0.8cm). Statistical wave properties and runup values are calculated, as well as bathymetry inversions using a relatively simple nonlinear correction to wave crest phase speed in the surf zone, illustrating the utility of drone-based lidar observations for nearshore processes.

Open access
Je-Yuan Hsu

Abstract

EM-APEX floats as autonomous vehicles have been used for profiling temperature, salinity, and current velocity for more than a decade. In the traditional method for processing horizontal current velocity from float measurements, signals of surface wave motion are removed as residuals. Here, a new data processing method is proposed for deriving the horizontal velocity of surface waves at the floats. Combined with the vertical acceleration measurements of waves, surface wave directional spectra E(f, θ) can be computed. This method is applied to the float measurements on the right of Typhoon Megi’s 2010 track. At 0.6 days before the passage of Megi’s eye to the floats, the fast-propagating swell may affect wind waves forced by the local storm wind. When the storm moves closer to the floats, the increasing wind speed and decreasing angle between wind and dominant wave direction may enhance the wind forcing and form a monomodal spectrum E(f). The peak frequency f p ~ 0.08 Hz and significant wave height > 10 m are found near the eyewall. After the passage of the eye to the floats, f p increases to >0.1 Hz. Although E(f) still has a single spectral peak at the rear-right quadrant of Megi, E(f, θ) at frequencies from 0.08 to 0.12 Hz has waves propagating in three different directions as a trimodal spectrum, partially due to the swell propagating from the rear-left quadrant. Enhancing the capability of EM-APEX floats to observe wave spectra is critical for exploring the roles of surface waves in the upper ocean dynamics in the future.

Open access
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 or human-occupied vehicle, and it can be 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.

Open access
Anita Freundorfer, Karl Lapo, Johann Schneider, and Christoph K. Thomas

Abstract

In the atmospheric boundary layer, phenomena exist with challenging properties such as spatial heterogeneity, particularly during stable weak wind situations. Studying spatially heterogeneous features requires spatially distributed measurements on fine spatial and temporal scales. Fiber-optic distributed sensing (FODS) can provide spatially distributed measurements, simultaneously offering a spatial resolution on the order of decimeters and a temporal resolution on the order of seconds. While FODS has already been deployed to study various variables, FODS wind direction sensing has only been demonstrated in idealized wind tunnel experiments. We present the first distributed observations of FODS wind directions from field data. The wind direction sensing is accomplished by using pairs of actively heated fiber-optic cables with cone-shaped microstructures attached to them. Here we present three different methods of calculating wind directions from the FODS measurements, two based on using combined wind speed and direction information and one deriving wind direction independently from FODS wind speed. For each approach, the effective temporal and spatial resolution is quantified using spectral coherence. With each method of calculating wind directions, temporal resolutions on the order of tens of seconds can be achieved. The accuracy of FODS wind directions was evaluated against a sonic anemometer, showing deviations of less than 15° most of the time. The applicability of FODS for wind direction measurements in different environmental conditions is tested by analyzing the dependence of FODS wind direction accuracy and observable scales on environmental factors. Finally, we demonstrate the potential of this technique by presenting a period that displays spatial and temporal structures in the wind direction.

Open access