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Jason M. Apke
,
Yoo-Jeong Noh
, and
Kristopher Bedka

Abstract

This study introduces a validation technique for quantitative comparison of algorithms that retrieve winds from passive detection of cloud- and water vapor–drift motions, also known as atmospheric motion vectors (AMVs). The technique leverages airborne wind-profiling lidar data collected in tandem with 1-min refresh-rate geostationary satellite imagery. AMVs derived with different approaches are used with accompanying numerical weather prediction model data to estimate the full profiles of lidar-sampled winds, which enables ranking of feature tracking, quality control, and height-assignment accuracy and encourages mesoscale, multilayer, multiband wind retrieval solutions. The technique is used to compare the performance of two brightness motion, or “optical flow,” retrieval algorithms used within AMVs, 1) patch matching (PM; used within operational AMVs) and 2) an advanced variational optical flow (VOF) method enabled for most atmospheric motions by new-generation imagers. The VOF AMVs produce more accurate wind retrievals than the PM method within the benchmark in all imager bands explored. It is further shown that image regions with low texture and multilayer-cloud scenes in visible and infrared bands are tracked significantly better with the VOF approach, implying VOF produces representative AMVs where PM typically breaks down. It is also demonstrated that VOF AMVs have reduced accuracy where the brightness texture does not advect with the mean wind (e.g., gravity waves), where the image temporal noise exceeds the natural variability, and when the height assignment is poor. Finally, it is found that VOF AMVs have improved performance when using fine-temporal refresh-rate imagery, such as 1- versus 10-min data.

Open access
Andre Amador
,
Sophia T. Merrifield
, and
Eric J. Terrill

Abstract

The present work details the measurement capabilities ofWave Glider Autonomous Surface Vehicles (ASVs) for research-grade meteorology, wave, and current data. Methodologies for motion compensation are described and tested, including a correction technique to account for Doppler shifting of the wave signal. Wave Glider measurements are evaluated against observations obtained fromWorld Meteorological Organization (WMO)-compliant moored buoy assets located off the coast of Southern California. The validation spans a range of field conditions and includes multiple deployments to assess the quality of vehicle-based observations. Results indicate that Wave Gliders can accurately measure wave spectral information, bulk wave parameters, water velocities, bulk winds, and other atmospheric variables with the application of appropriate motion compensation techniques. Measurement errorswere found to be comparable to those from reference moored buoys and within WMO operational requirements. The findings of this study represent a step towards enabling the use of ASV-based data for the calibration and validation of remote observations and assimilation into forecast models.

Restricted access
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Free access
Julia Muchowski
,
Lars Umlauf
,
Lars Arneborg
,
Peter Holtermann
,
Elizabeth Weidner
,
Christoph Humborg
, and
Christian Stranne

Abstract

Stratified oceanic turbulence is strongly intermittent in time and space, and therefore generally underresolved by currently available in situ observational approaches. A promising tool to at least partly overcome this constraint are broadband acoustic observations of turbulent microstructure that have the potential to provide mixing parameters at orders of magnitude higher resolution compared to conventional approaches. Here, we discuss the applicability, limitations, and measurement uncertainties of this approach for some prototypical turbulent flows (stratified shear layers, turbulent flow across a sill), based on a comparison of broadband acoustic observations and data from a free-falling turbulence microstructure profiler. We find that broadband acoustics are able to provide a quantitative description of turbulence energy dissipation in stratified shear layers (correlation coefficient r = 0.84) if the stratification parameters required by the method are carefully preprocessed. Essential components of our suggested preprocessing algorithm are 1) a vertical low-pass filtering of temperature and salinity profiles at a scale slightly larger than the Ozmidov length scale of turbulence and 2) an automated elimination of weakly stratified layers according to a gradient threshold criterion. We also show that in weakly stratified conditions, the acoustic approach may yield acceptable results if representative averaged vertical temperature and salinity gradients rather than local gradients are used. Our findings provide a step toward routine turbulence measurements in the upper ocean from moving vessels by combining broadband acoustics with in situ CTD profiles.

Open access
Jian Xu
,
Xing Wang
,
Ping Liu
, and
Qiaoyu Duan

Abstract

This article develops a novel event-triggered sliding mode control (ETSMC) approach with variable threshold to deal with trajectory tracking matters of autonomous underwater vehicles (AUVs) accompanied by actuator saturation and external disturbances, which can effectively reduce the communication burden between the controller and actuator. The proposed scheme will be very practical when some extreme situations occur. First, the closed-loop system is split into two parts: fixed terms determined by the system itself and nonlinear terms caused by uncertain factors. The nonlinear terms are estimated through adaptive technique. Then the apposite event-triggered mechanism, adaptive laws, and modeled actuator saturation characteristics are designed. The correctness of the presented scheme is illustrated via the stability analysis in the sequel, and the Zeno phenomenon is certificated to be excluded simultaneously. Finally, two different reference motion trajectories are adopted in the simulation experiments, which can indicate that the proposed ETSMC possesses performance superiority and only requires to consume a small amount of communication resources in trajectory tracking control of AUVs.

Significance Statement

Through the research of this article, we propose a novel event-triggered sliding mode control method with variable threshold applied to autonomous underwater vehicles (AUVs). When conducting ocean exploration work, we usually need the AUVs to follow particular trajectories. By using the proposed method, it can greatly reduce the loss of communication resources inside the system.

Restricted access
Giuseppe Zibordi
,
Davide D’Alimonte
, and
Tamito Kajiyama

Abstract

Quality control (QC) practices are a fundamental requirement for any measurement program targeting the delivery of high-quality data. In agreement with such a need, the Ocean Color component of the Aerosol Robotic Network (AERONET-OC) includes a number of QC steps ensuring the delivery of normalized water-leaving radiance L WN spectra at incremental accuracy levels identified as level 1.0, level 1.5, and level 2.0. Currently, the final QC step allowing for rising level 1.5 L WN spectra to level 2.0 implies the execution of an expert-based procedure, which is extremely time consuming and naturally undergoes subjective decisions on dubious cases. These limitations solicited the development of an automated procedure, so-called A –QC L WN , mimicking the steps supporting an expert analyst during the final QC of AERONET-OC L WN spectra. A –QC L WN applies hierarchical tests to check (i) the relative consistency of level 1.5 L WN spectra (called candidates) with respect to L WN reference spectra (called prototypes) constructed using L WN spectra formerly and independently quality controlled; (ii) the absence of any pronounced spectral feature in portions of each L WN candidate spectrum expected to exhibit a regular shape; and additionally, when applicable, (iii) the temporal consistency of the L WN candidate spectrum with respect to close-in-time spectra as a criterion to further strengthen the quality of data. A –QC L WN performance has been verified using L WN spectra from AERONET-OC measurement sites representative of various water types embracing oligotrophic/mesotrophic waters dominated by chlorophyll-a concentration and coastal waters exhibiting increasing levels of optical complexity. A –QC L WN has shown an acceptance rate of AERONET-OC level 1.5 L WN candidate spectra varying between approximately 89% and 93% with agreement in the range of 88%–93% with respect to the L WN spectra independently quality controlled through the expert-based procedure. The additional capability of A –QC L WN to rank the fully quality-controlled L WN spectra combining weights depending on the various tests, anticipates the possibility to best support applications with diverse accuracy needs. Finally, acceptance rates of A –QC L WN for L WN prototype spectra built using level 1.5 data, an alternative to fully quality-controlled level 2.0, have shown values generally increased by less than 1%. This indicates the possibility to lessen the constraint implying the existence of reference level 2.0 L WN data for the relative-consistency test at the expense of a fairly low reduction in accuracy.

Open access
Ibrahim Ibrahim
,
Gregory A. Kopp
, and
David M. L. Sills

Abstract

The current study develops a variant of the VAD method to retrieve thunderstorm peak event velocities using low-elevation WSR-88D radar scans. The main challenge pertains to the localized nature of thunderstorm winds which complicates single-Doppler retrievals as it dictates the use of a limited spatial scale. Since VAD methods assume constant velocity in the fitted section, it is important that retrieved sections do not contain background flow. Accordingly, the current study proposes an image processing method to partition scans into regions, representing events and the background flows, that can be retrieved independently. The study compares the retrieved peak velocities to retrievals using another VAD method. The proposed technique is found to estimate peak event velocities that are closer to measured ASOS readings, making it more suitable for historical analysis. The study also compares the results of retrievals from over 2600 thunderstorm events from 19 radar-ASOS station combinations that are less than 10 km away from the radar. Comparisons of probability distributions of peak event velocities for ASOS readings and radar retrievals showed good agreement for stations within 4 km from the radar while more distant stations had a higher bias towards retrieved velocities compared to ASOS velocities. The mean absolute error for velocity magnitude increases with height ranging between 1.5 and 4.5 m s−1. A proposed correction based on the exponential trend of mean errors was shown to improve the probability distribution comparisons, especially for higher velocity magnitudes.

Open access
Chunying Liu
,
Eric Freeman
,
Elizabeth C. Kent
,
David I. Berry
,
Steven J. Worley
,
Shawn R. Smith
,
Boyin Huang
,
Huai-min Zhang
,
Thomas Cram
,
Zaihua Ji
,
Mathieu Ouellet
,
Isabelle Gaboury
,
Frank Oliva
,
Axel Andersson
,
William E. Angel
,
Angela R. Sallis
, and
Adedoja Adeyeye

Abstract

This paper describes the new International Comprehensive Ocean–Atmosphere Data Set (ICOADS) near-real-time (NRT) release (R3.0.2), with greatly enhanced completeness over the previous version (R3.0.1). R3.0.1 had been operationally produced monthly from January 2015 onward, with input data from the World Meteorological Organization (WMO) Global Telecommunication Systems (GTS) transmissions in the Traditional Alphanumeric Codes (TAC) format. Since the release of R3.0.1, however, many observing platforms have changed, or are in the process of transitioning, to the Binary Universal Form for Representation of Meteorological Data (BUFR) format. R3.0.2 combines input data from both BUFR and TAC formats. In this paper, we describe input data sources; the BUFR decoding process for observations from drifting buoys, moored buoys, and ships; and the data quality control of the TAC and BUFR data streams. We also describe how the TAC and BUFR streams were merged to upgrade R3.0.1 into R3.0.2 with duplicates removed. Finally, we compare the number of reports and spatial coverage of essential climate variables (ECVs) between R3.0.1 and R3.0.2. ICOADS NRT R3.0.2 shows both quantitative and qualitative gains from the inclusion of BUFR reports. The number of observations in R3.0.2 increased by nearly 1 million reports per month, and the coverage of buoy and ship sea surface temperatures (SSTs) on monthly 2° × 2° grids increased by 20%. The number of reported ECVs also increased in R3.0.2. For example, observations of SST and sea level pressure (SLP) increased by around 30% and 20%, respectively, as compared to R3.0.1, and salinity is a new addition to the ICOADS NRT product in R3.0.2.

Significance Statement

The International Comprehensive Ocean–Atmosphere Data Set (ICOADS) is the largest collection of surface marine observations spanning from 1662 to the present. A new version, ICOADS near-real-time 3.0.2, includes data transmitted in the Binary Universal Form for Representation of Meteorological Data (BUFR) format, in combination with Traditional Alphanumeric Codes (TAC) data. Many of the organizations that report observations in near–real time have moved to BUFR, so this update brings ICOADS into alignment with collections and archives of these international data distributions. By including the BUFR reports, the number of observations in the upgraded version of ICOADS increased by nearly one million reports per month and spatial coverage of buoy and ship SSTs increased by 20% over the previous version.

Open access
Katrina S. Virts
and
William J. Koshak

Abstract

Performance assessments of the Geostationary Lightning Mapper (GLM) are conducted via comparisons with independent observations from both satellite-based sensors and ground-based lightning detection (reference) networks. A key limitation of this evaluation is that the performance of the reference networks is both imperfect and imperfectly known, such that the true performance of GLM can only be estimated. Key GLM performance metrics such as detection efficiency (DE) and false alarm rate (FAR) retrieved through comparison with reference networks are affected by those networks’ own DE, FAR, and spatiotemporal accuracy, as well as the flash matching criteria applied in the analysis.

This study presents a Monte Carlo simulation-based inversion technique that is used to quantify how accurately the reference networks can assess GLM performance, as well as suggest the optimal matching criteria for estimating GLM performance. This is accomplished by running simulations that clarify the specific effect of reference network quality (i.e., DE, FAR, spatiotemporal accuracy, and the geographical patterns of these attributes) on the retrieved GLM performance metrics. Baseline reference network statistics are derived from the Earth Networks Global Lightning Network (ENGLN) and the Global Lightning Dataset (GLD360).

Geographic simulations indicate that the retrieved GLM DE is underestimated, with absolute errors ranging from 11% to 32%, while the retrieved GLM FAR is overestimated, with absolute errors of approximately 16-44%. GLM performance is most severely underestimated in the South Pacific. These results help quantify and bound the actual performance of GLM and the attendant uncertainties when comparing GLM to imperfect reference networks.

Open access