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Shohei Morino, Naoyuki Kurita, Naohiko Hirasawa, Hideaki Motoyama, Konosuke Sugiura, Matthew Lazzara, David Mikolajczyk, Lee Welhouse, Linda Keller, and George Weidner

Abstract

Surface temperature measurements with naturally ventilated (NV) sensors over the Antarctic Plateau are largely subject to systematic errors due to solar radiative heating. Here we examined the radiative heating error in Dronning Maud Land on the East Antarctic Plateau using both the newly installed automatic weather stations (AWSs) at NDF and Relay Station and the existing AWSs at Relay Station and Dome Fuji. Two types of NV shields were used in these AWSs; a multi-plate radiation shield and a simple cylinder-shaped shield. In austral summer, the temperature bias between the force ventilated (FV) sensor and the NV sensor never reached zero due to continuous sunlight. The hourly mean temperature errors reached up to 8°C at noon on a sunny day with weak wind conditions. The errors increased linearly with increasing reflected shortwave radiation and decreased non-linearly with increasing wind speed. These features were observed in both the multi-plate and the cylinder-shaped shields. The magnitude of the errors of multi-plate shield was much larger than that of the cylinder-shaped shield. To quantify the radiative errors, we applied an existing correction model based on the regression approach and successfully reduced the errors more than 70% after the correction. This indicates that we can use the corrected temperature data instead of quality controlled data, which removed warmbias during weak winds in inland Dronning Maud Land.

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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, that 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 flashes. 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% to 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.

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David T. Walker and Kelsey Brunner

Abstract

This paper describes a variational data assimilation algorithm based on the SWAN near shore 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 to independent observation data. The results compare favorably to the independent data with overall RMS errors of 10–20 percent for significant wave height, about half a second for mean wave period, and as much as 3–4 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.

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Douglas Mach and Katrina Virts

Abstract

We have developed a technique to estimate the three-dimensional (3D) location of lightning optical pulses based on the stereo view of common lightning pulses from two different orbital instruments. The technique only requires the satellite position and the look vector to the lightning optical source. An example dataset of the Geostationary Lightning Mappers (GLMs) on GOES-16 and GOES-17 from 10 June 2019 is used to illustrate the technique. For this dataset, we find that the values for the stereo determination of cloud top altitudes are on average lower by 740 m than the ones calculated from the lightning ellipsoid that is currently applied during geolocation. When we compare the locations to the Advanced Baseline Imager (ABI) Cloud Height Algorithm (ACHA), we find that our technique also produces slightly lower altitude values by 240 m. There is greater spread in our technique than either the lightning ellipsoid or the ABI cloud-top height that is likely due to the incorrect pairing of Groups between the two GLMs and the 8 to 14 km resolution in the Group locations. Based on GLM location errors derived from comparisons to ground truth sources, the uncertainty in the radial location determined by the stereo location technique is 5.2 km, while the altitude uncertainty is 4.0 km. The technique can be used to 3D map lightning or other optical sources such as bolides and other upper atmospheric optical phenomena from any two orbital sensors with overlapping fields of view.

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Charles-Antoine Guérin, Dylan Dumas, Anne Molcard, Céline Quentin, Bruno Zakardjian, Anthony Gramoullé, and Maristella Berta

Abstract

We report on the installation and first results of one compact oceanographic radar in the region of Nice for a long-term observation of the coastal surface currents in the North-West Mediterranean Sea. We describe the specific processing and calibration techniques that were developed at the laboratory to produce high-quality radial surface current maps. In particular, we propose an original self-calibration technique of the antenna patterns, which is based on the sole analysis of the database and does not require any shipborne transponder or other external transmitters. The relevance of the self-calibration technique and the accuracy of inverted surface currents have been assessed with the launch of 40 drifters that remained under the radar coverage for about 10 days.

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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 PRISM Climate Group releases eight versions of a day’s precipitation grid, from 24 hours after day’s end to six months 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. Finally, 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 underway to improve station metadata, refine interpolation methods by producing climatologies targeted to specific storm conditions, and employ higher-resolution radar products.

Open access
Agustinus Ribal, Ali Tamizi, and Ian R. Young

Abstract

Four scatterometers, namely, MetOp-A, MetOp-B, ERS-2, and OceanSat-2 were recalibrated against combined National Data Buoy Center (NDBC) data and aircraft Stepped Frequency Microwave Radiometer (SFMR) data from hurricanes. As a result, continuous calibration relations over the wind speed range from 0 to 45 m s−1 were developed. The calibration process uses matchup criteria of 50 km and 30 min for the buoy data. However, due to the strong spatiotemporal wind speed gradients in hurricanes, a method that considers both scatterometer and SFMR data in a storm-centered translating frame of reference is adopted. The results show that although the scatterometer radar cross section is degraded at high wind speeds, it is still possible to recover wind speed data using the recalibration process. Data validation between the scatterometers shows that the calibration relations produce consistent results across all scatterometers and reduce the bias and root-mean-square error compared to previous calibrations. In addition, the results extend the useful range of scatterometer measurements to as high as 45 m s−1.

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Lillian Muir, Chris Roman, David Casagrande, and Steven D’Hondt

Abstract

The Deep Autonomous Profiler (DAP) is a full-ocean-depth profiler rated to 11 km. Its hydrographic profiles and water samples can provide information on physical oceanographic properties, seawater composition, and biological communities at every depth in the ocean. Designed around a 24-bottle rosette, the DAP is an untethered system able to autonomously collect temperature, salinity, and oxygen profiles, as well as water samples. An adaptive sampling method was developed to analyze the water-column data to identify and sample desired features while under way. Acoustic ranging-only tracking is used to monitor and geolocate the system underwater. In September 2018 the vehicle was tested to 8377 m in the Puerto Rico Trench. The DAP was able to generate full-ocean-depth profiles and collect water samples at both preset and adaptively determined depths. To demonstrate the utility of the DAP, we radiocarbon dated the deepest water sampled in the Puerto Rico Trench, providing the first direct evidence of hadal water-mass age in the trench: 318 ± 25 yr. This paper presents an overview of the DAP system and the Puerto Rico Trench sea trials.

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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 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