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Mark A. Askelson, Chris J. Theisen, and Randall S. Johnson

Abstract

Owing to their ease of use, “simplified” propagation models, like the equivalent Earth model, are commonly employed to determine radar data locations. With the assumption that electromagnetic rays follow paths of constant curvature, which is a fundamental assumption in the equivalent Earth model, propagation equations that do not depend upon the spatial transformation that is utilized in the equivalent Earth model are derived. This set of equations provides the true constant curvature solution and is less complicated, conceptually, as it does not depend upon a spatial transformation. Moreover, with the assumption of constant curvature, the relations derived herein arise naturally from ray tracing relations. Tests show that this new set of equations is more accurate than the equivalent Earth equations for a “typical” propagation environment in which the index of refraction n decreases linearly at the rate dn/dh = −1/4a, where h is height above ground and a is Earth’s radius. Moreover, this new set of equations performs better than the equivalent Earth equations for an exponential reference atmosphere, which provides a very accurate representation of the average atmospheric n structure in the United States. However, with this n profile the equations derived herein, the equivalent Earth equations, and the relation associated with a flat Earth constant curvature model produce relatively large height errors at low elevations and large ranges. Taylor series approximations of the new equations are examined. While a second-order Taylor series approximation for height performs well under “typical” propagation conditions, a convenient Taylor series approximation for great circle distance was not obtained.

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Tao Xing and Yikai Yang

Abstract

Complex topography and the Kuroshio eddy-shedding process produce active mesoscale eddy activity in the South China Sea (SCS). Three eddy detection and tracking methods, the Okubo–Weiss (O-W), vector-geometry (V-G), and winding-angle (W-A) algorithms, have been widely applied for eddy identification. This study provides a comprehensive assessment of the O-W, V-G, and W-A methods in the SCS, including their detection, statistical analysis, and tracking capabilities. The mean successful detection rates of the O-W, V-G, and W-A methods are 51.9%, 56.8%, and 61.4%, respectively. The O-W and V-G methods preferentially detect eddies with medium radii (½°–1°), whereas the W-A method tends to detect eddies with larger radii (>1°). The V-G method identifies an excessive number of weak (radius < ⅓°) eddylike structures in the SCS, accounting for 48.2% of the total eddy number. The highest mean excessive detection rate of the V-G method biases the data on eddy number, probability, and propagation direction. With the lowest mean successful tracking rate (STR), the O-W method might not be suitable for tracking long-lived eddies in the SCS. The V-G method performs well with regard to the overtracking issue and has the lowest mean questionable tracking rate of 1.1%. Among the three methods, the W-A method tracks eddies most accurately, with the highest mean STR of 80.6%. Overall, the W-A method produces reasonable statistical eddy characteristics and eddy tracking results. Each method has advantages and disadvantages, and researchers should choose wisely according to their needs.

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Daosheng Wang, Haidong Pan, Lin Mu, Xianqing Lv, Bing Yan, and Hua Yang

Abstract

The coastal ocean sea level (SL) variations result from multiscale processes and are dominated by SL changes due to meteorological forcing. In this study, a new methodology, which combines inverted barometer correction and regression analysis (IBR), is developed to estimate the coastal ocean response to meteorological forcing in shallow water. The response is taken as the combination of the static ocean response calculated using the inverted barometer formula and the dynamic ocean response estimated using the multivariable linear regression involving atmospheric pressure and the wind component in the dominant wind orientation. IBR was implemented to estimate the coastal ocean response at two stations, E1 and E2, in Bohai Bay, China. The analyzed results indicate that at both stations, the adjusted SLs are related more to the regional wind, which is the averaged value of ERA-Interim data in Bohai Bay, than to the local wind. The estimated response using IBR with the regional meteorological forcing is much closer to the observed values than other methods, including the classical inverted barometer correction, the dynamic atmospheric correction, the multivariable linear regression, and the IBR with local forcing. The deviations between the observed values and the estimated values using IBR with regional meteorological forcing can be primarily attributed to remote wind. This case study indicates that IBR is a feasible and relatively effective method to estimate the coastal ocean response to meteorological forcing in shallow water.

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Sergey Y. Matrosov

Abstract

Dual-frequency millimeter-wavelength radar observations in snowfall are analyzed in order to evaluate differences in conventional polarimetric radar variables such as differential reflectivity (Z DR) specific differential phase shift (K DP) and linear depolarization ratio (LDR) at traditional cloud radar frequencies at Ka and W bands (~35 and ~94 GHz, correspondingly). Low radar beam elevation (~5°) measurements were performed at Oliktok Point, Alaska, with a scanning fully polarimetric radar operating in the horizontal–vertical polarization basis. This radar has the same gate spacing and very close beam widths at both frequencies, which largely alleviates uncertainties associated with spatial and temporal data matching. It is shown that observed Ka- and W-band Z DR differences are, on average, less than about 0.5 dB and do not have a pronounced trend as a function of snowfall reflectivity. The observed Z DR differences agree well with modeling results obtained using integration over nonspherical ice particle size distributions. For higher signal-to-noise ratios, K DP data derived from differential phase measurements are approximately scaled as reciprocals of corresponding radar frequencies indicating that the influence of non-Rayleigh scattering effects on this variable is rather limited. This result is also in satisfactory agreement with data obtained by modeling using realistic particle size distributions. Observed Ka- and W-band LDR differences are strongly affected by the radar hardware system polarization “leak” and are generally less than 4 dB. Smaller differences are observed for higher depolarizations, where the polarization “leak” is less pronounced. Realistic assumptions about particle canting and the system polarization isolation lead to modeling results that satisfactorily agree with observational dual-frequency LDR data.

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Suneil Iyer, Kyla Drushka, and Luc Rainville

Abstract

As part of the second Salinity Processes in the Upper Ocean Regional Study (SPURS-2), the ship-towed Surface Salinity Profiler (SSP) was used to measure near-surface turbulence and stratification on horizontal spatial scales of tens of kilometers over time scales of hours, resolving structures outside the observational capabilities of autonomous or Lagrangian platforms. Observations of microstructure variability of temperature were made at approximately 37 cm depth from the SSP. The platform can be used to measure turbulent kinetic energy dissipation rate when the upper ocean is sufficiently stratified by calculating temperature gradient spectra from the microstructure data and fitting to low-wavenumber theoretical Batchelor spectra. Observations of dissipation rate made across a range of wind speeds under 12 m s−1 were consistent with the results of previous studies of near-surface turbulence and with existing turbulence scalings. Microstructure sensors mounted on the SSP can be used to investigate the spatial structure of near-surface turbulence. This provides a new means to study the connections between near-surface turbulence and the larger-scale distributions of heat and salt in the near-surface layer of the ocean.

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R. Giles Harrison, Keri A. Nicoll, Douglas J. Tilley, Graeme J. Marlton, Stefan Chindea, Gavin P. Dingley, Pejman Iravani, David J. Cleaver, Jonathan L. du Bois, and David Brus

Abstract

Electric charge is always present in the lower atmosphere. If droplets or aerosols become charged, their behavior changes, influencing collision, evaporation, and deposition. Artificial charge release is an unexplored potential geoengineering technique for modifying fogs, clouds, and rainfall. Central to evaluating these processes experimentally in the atmosphere is establishing an effective method for charge delivery. A small charge-delivering remotely piloted aircraft has been specially developed for this, which is electrically propelled. It carries controllable bipolar charge emitters (nominal emission current ±5 μA) beneath each wing, with optical cloud and meteorological sensors integrated into the airframe. Meteorological and droplet measurements are demonstrated to 2 km altitude by comparison with a radiosonde, including within cloud, and successful charge emission aloft verified by using programmed flight paths above an upward-facing surface electric field mill. This technological approach is readily scalable to provide nonpolluting fleets of charge-releasing aircraft, identifying and targeting droplet regions with their own sensors. Beyond geoengineering, agricultural, and biological aerosol applications, safe ionic propulsion of future electric aircraft also requires detailed investigation of charge effects on natural atmospheric droplet systems.

Open access
Temple R. Lee and Sandip Pal

Abstract

Rawinsonde observations have long been used to estimate the atmospheric boundary layer depth (BLD), which is an important parameter for monitoring air quality, dispersion studies, weather forecast models, and inversion systems for estimating regional surface–atmosphere fluxes of tracers. Although many approaches exist for deriving the BLDs from rawinsonde observations, the bulk Richardson approach has been found to be most appropriate. However, the impact of errors in the measured thermodynamic and kinematic fields on the estimated BLDs remains unexplored. We argue that quantifying BLD error (δBLD) estimates is equally as important as the BLDs themselves. Here we quantified δBLD by applying the bulk Richardson method to 35 years of rawinsonde data obtained from three stations in the United States: Sterling, Virginia; Amarillo, Texas; and Salt Lake City, Utah. Results revealed similar features in terms of their respective errors. A −2°C bias in temperature yielded a mean δBLD ranging from −15 to 200 m. A +2°C bias in temperature yielded a mean δBLD ranging from −214 to +18 m. For a −5% relative humidity bias, the mean δBLD ranged from −302 to +7 m. For a +5% relative humidity bias, the mean δBLD ranged from +2 to +249 m. Differences of ±2 m s−1 in the winds yielded BLD errors of ~±300 m. The δBLD increased as a function of BLD when introducing errors to the thermodynamic fields and decreased as a function of BLD when introducing errors to the kinematic fields. These findings expand upon previous work evaluating rawinsonde-derived δBLD by quantifying δBLD arising from rawinsonde-derived thermodynamic and kinematic measurements. Knowledge of δBLD is critical in, for example, intercomparison studies where rawinsonde-derived BLDs are used as references.

Open access
Yang He, Zheng Sheng, Yanwei Zhu, and Mingyuan He

Abstract

Noise removal is a key issue in the retrieval of turbulence from meteorological radiosonde data using the method proposed by Thorpe. Only by reducing as much as possible the influence of noise in the potential temperature fluctuations can the retrieval results reflect the turbulence characteristics of the real atmosphere. In this paper, an adaptive variational mode decomposition (VMD) method is proposed that is used to remove noise fluctuations from the potential temperature profile, and particle swarm optimization and mutual information are used to optimize the preset VMD parameters. The Thorpe method is applied to the denoised potential temperature profile to identify and characterize turbulent regions. The results show that the adaptive VMD method is very effective for denoising the potential temperature profile in both simulation experiments and actual detection data. The real turbulence overturn can be selected from the inversions by optimal smoothing and statistical tests. This method is an improvement on the Wilson method and allows the Thorpe method to be applied to daytime sounding data, avoiding the confusion between noise and turbulence that results in the distortion of the turbulence scale.

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Casey R. Densmore, Steven R. Jayne, and Elizabeth R. Sanabia

Abstract

Airborne expendable bathythermographs (AXBTs) are air-launched, single-use temperature–depth probes that telemeter temperature observations as VHF-modulated frequencies. This study describes the AXBT Real-Time Editing System (ARES), which is composed of two components: the ARES Data Acquisition System, which receives telemetered temperature–depth profiles with no external hardware other than a VHF radio receiver, and the ARES Profile Editing System, which quality controls AXBT temperature–depth profiles. The ARES Data Acquisition System performs fast Fourier transforms on windowed segments of the demodulated signal transmitted from the AXBT. For each segment, temperature is determined from peak frequency and depth from elapsed time since profile start. Valid signals are distinguished from noise by comparing peak signal levels and signal-to-noise ratios to predetermined thresholds. When evaluated using 387 profiles, the ARES Data Acquisition System produced temperature–depth profiles nearly identical to those generated using a Sippican MK-21 processor, while reducing the amount of noise from VHF interference included in those profiles. The ARES Profile Editor applies a series of automated checks to identify and correct common profile discrepancies before displaying the profile on an editing interface that provides simple user controls to make additional corrections. When evaluated against 1177 tropical Atlantic and Pacific AXBT profiles, the ARES automated quality control system successfully corrected 87% of the profiles without any required manual intervention. Necessary future work includes improvements to the automated quality control algorithm and algorithm evaluation against a broader dataset of temperature–depth profiles from around the world across all seasons.

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Peter Rogowski, Mark Otero, Joel Hazard, Thomas Muschamp, Scott Katz, and Eric Terrill

Abstract

Accurate surface meteorological (MET) observations reported reliably and in near–real time remain a critical component of on-scene environmental observation systems. Presented is a system developed by Scripps Institution of Oceanography that allows for rapid, global deployment of ground-based weather observations to support both timely decision-making and collection of high-quality weather time series for science or military applications in austere environments. Named the Expeditionary Meteorological (XMET), these weather stations have been deployed in extreme conditions devoid of infrastructure ranging from tropical, polar, maritime, and desert environments where near continuous observations were reported. To date, over 1 million weather observations have been collected during 225 deployments around the world with a data report success rate of 99.5%. XMET had its genesis during Operation Iraqi Freedom (OIF), when the U.S. Marine Corps 3rd Marine Aircraft Wing identified an immediate capability gap in environmental monitoring of their operation area due to high spatiotemporal variability of dust storms in the region. To address the sensing gap, XMET was developed to be a portable, expendable, ruggedized, self-contained, bidirectional, weather observation station that can be quickly deployed anywhere in the world to autonomously sample and report aviation weather observations. This paper provides an overview of the XMETs design, reliability in different environments, and examples of unique meteorological events that highlight both the unit’s reliability and ability to provide quality time series. The overview shows expeditionary MET sensing systems, such as the XMET, are able to provide long-term continuous observational records in remote and austere locations essential for regional spatiotemporal MET characterization.

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