961 research outputs found
Improved Micro Rain Radar snow measurements using Doppler spectra post-processing
The Micro Rain Radar 2 (MRR) is a compact Frequency Modulated Continuous Wave (FMCW) system that operates at 24 GHz. The MRR is a low-cost, portable radar system that requires minimum supervision in the field. As such, the MRR is a frequently used radar system for conducting precipitation research. Current MRR drawbacks are the lack of a sophisticated post-processing algorithm to improve its sensitivity (currently at +3 dBz), spurious artefacts concerning radar receiver noise and the lack of high quality Doppler radar moments. Here we propose an improved processing method which is especially suited for snow observations and provides reliable values of effective reflectivity, Doppler velocity and spectral width. The proposed method is freely available on the web and features a noise removal based on recognition of the most significant peak. A dynamic dealiasing routine allows observations even if the Nyquist velocity range is exceeded. Collocated observations over 115 days of a MRR and a pulsed 35.2 GHz MIRA35 cloud radar show a very high agreement for the proposed method for snow, if reflectivities are larger than −5 dBz. The overall sensitivity is increased to −14 and −8 dBz, depending on range. The proposed method exploits the full potential of MRR's hardware and substantially enhances the use of Micro Rain Radar for studies of solid precipitation
Cloud droplet size distribution broadening during diffusional growth: Ripening amplified by deactivation and reactivation
Cloud droplet size distributions (CDSDs), which are related to cloud albedo and rain formation, are usually broader in warm clouds than predicted from adiabatic parcel calculations. We investigate a mechanism for the CDSD broadening using a moving-size-grid cloud parcel model that considers the condensational growth of cloud droplets formed on polydisperse, submicrometer aerosols in an adiabatic cloud parcel that undergoes vertical oscillations, such as those due to cloud circulations or turbulence. Results show that the CDSD can be broadened during condensational growth as a result of Ostwald ripening amplified by droplet deactivation and reactivation, which is consistent with early work. The relative roles of the solute effect, curvature effect, deactivation and reactivation on CDSD broadening are investigated. Deactivation of smaller cloud droplets, which is due to the combination of curvature and solute effects in the downdraft region, enhances the growth of larger cloud droplets and thus contributes particles to the larger size end of the CDSD. Droplet reactivation, which occurs in the updraft region, contributes particles to the smaller size end of the CDSD. In addition, we find that growth of the largest cloud droplets strongly depends on the residence time of cloud droplet in the cloud rather than the magnitude of local variability in the supersaturation fluctuation. This is because the environmental saturation ratio is strongly buffered by numerous smaller cloud droplets. Two necessary conditions for this CDSD broadening, which generally occur in the atmosphere, are as follows: (1) droplets form on aerosols of different sizes, and (2) the cloud parcel experiences upwards and downwards motions. Therefore we expect that this mechanism for CDSD broadening is possible in real clouds. Our results also suggest it is important to consider both curvature and solute effects before and after cloud droplet activation in a cloud model. The importance of this mechanism compared with other mechanisms on cloud properties should be investigated through in situ measurements and 3-D dynamic models
Observations of the variability of shallow trade wind cumulus cloudiness and mass flux
Two years of ground-based remote sensing observations are used to study the vertical structure of marine cumulus near the island of Barbados, including their cloud fraction and mass flux profile. Daily radar derived cloud fraction profiles peak at different height levels depending on the depth of the cumuli and thus the extent to which they precipitate. Nonprecipitating cumuli have a peak cloud fraction of about 5% near mean cloud base (700m), whereas precipitating cumuli tend to have a peak of only 2% near cloud base. Nineteen percent of the precipitating cumuli are accompanied by large cloud fractions near the detrainment level of cumulus tops (similar to 1700m). Day-to-day variations in cloud fraction near cloud base are modest (similar to 3%). Nonprecipitating cumuli have their largest reflectivities near cloud top and an ascending core surrounded by a subsiding shell. Precipitating cumuli with enhanced elevated cloudiness (stratiform outflow) are deeper and contain larger vertical gradients in reflectivity and Doppler velocity than precipitating cumuli without such outflow. Bulk (3h) statistics reveal that nonprecipitating shallow cumuli are active and organized. They contain on average 79% in-cloud updrafts with 86% of them being organized in large coherent structures contributing to a maximum updraft mass flux of 8-36gm(-2)s(-1) just above cloud base. Alternatively, downdrafts contribute insignificantly to the mass flux and show little vertical and temporal variability (0-7gm(-2)s(-1)). Complementary Raman lidar information suggests that updraft mass flux profile slope is inversely related to environmental relative humidity
Universal Programmable Quantum Circuit Schemes to Emulate an Operator
Unlike fixed designs, programmable circuit designs support an infinite number
of operators. The functionality of a programmable circuit can be altered by
simply changing the angle values of the rotation gates in the circuit. Here, we
present a new quantum circuit design technique resulting in two general
programmable circuit schemes. The circuit schemes can be used to simulate any
given operator by setting the angle values in the circuit. This provides a
fixed circuit design whose angles are determined from the elements of the given
matrix-which can be non-unitary-in an efficient way. We also give both the
classical and quantum complexity analysis for these circuits and show that the
circuits require a few classical computations. They have almost the same
quantum complexities as non-general circuits. Since the presented circuit
designs are independent from the matrix decomposition techniques and the global
optimization processes used to find quantum circuits for a given operator, high
accuracy simulations can be done for the unitary propagators of molecular
Hamiltonians on quantum computers. As an example, we show how to build the
circuit design for the hydrogen molecule.Comment: combined with former arXiv:1207.174
Particle inertial effects on radar Doppler spectra simulation
Radar Doppler spectra observations provide a wealth of information about cloud and precipitation microphysics and dynamics. The interpretation
of these measurements depends on our ability to simulate these observations
accurately using a forward model. The effect of small-scale turbulence on the radar Doppler spectra shape has been traditionally treated by implementing the convolution process on the hydrometeor reflectivity spectrum and environmental turbulence. This approach assumes that all the particles in the radar sampling volume respond the same to turbulent-scale velocity fluctuations and neglects the particle inertial effect. Here, we investigate the inertial effects of liquid-phase particles on the forward modeled radar Doppler spectra. A physics-based simulation (PBS) is developed to demonstrate that big droplets, with large inertia, are unable to follow the rapid change of the velocity field in a turbulent environment. These findings are incorporated into a new radar Doppler spectra simulator. Comparison between the traditional and newly formulated radar Doppler spectra simulators indicates that the conventional simulator leads to an unrealistic broadening of the spectrum, especially in a strong turbulent environment. This study provides clear evidence to illustrate the droplet inertial effect on radar Doppler spectrum and develops a physics-based simulator framework to accurately emulate the Doppler spectrum for a given droplet size distribution (DSD) in a turbulence field. The proposed simulator has various potential applications for the cloud and precipitation studies, and it provides a valuable tool to decode the cloud microphysical and dynamical properties from Doppler radar observation.</p
Noise-based core monitoring and diagnostics: overview of the cortex project
This paper gives an overview of the CORTEX project, which is a Research and Innovation Action
funded by the European Union in the Euratom 2016-2017 work program, under the Horizon 2020
framework. CORTEX, which stands for CORe monitoring Techniques and EXperimental validation
and demonstration, aims at developing an innovative core monitoring technique that allows
detecting anomalies in nuclear reactors, such as excessive vibrations of core internals, flow
blockage, coolant inlet perturbations, etc. The technique is based on primarily using the inherent
fluctuations in neutron flux recorded by in-core and ex-core instrumentation (often referred to as
neutron noise), from which the anomalies will be differentiated depending on their type, location
and characteristics. In addition to be non-intrusive and not requiring any external perturbation of the
system, the method allows the detection of operational problems at a very early stage. Proper
actions could thus be taken by utilities before such problems have any adverse effect on plant safety
and reliability
Electrocardiographic and Electrophysiologic Characteristics of Ventricular Extrasystoles Arising from the Aortomitral Continuity
Left ventricular outflow tract arrhythmias originating from the aortomitral continuity, the left coronary cusp, the superior basal septum, and the epicardial left ventricular summit display common electrocardiographic and electrophysiological features, probably due to the close proximity of those locations. Catheter ablation of these arrhythmias can be challenging. The case of a 68-year-old male with frequent premature ventricular extrasystoles arising from the aortomitral continuity of the basal left ventricle is described. The electrocardiographic and electrophysiologic characteristics of this arrhythmia are discussed
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A High Resolution Hydrometer Phase Classifier Based on Analysis of Cloud Radar Doppler Spectra.
The lifecycle and radiative properties of clouds are highly sensitive to the phase of their hydrometeors (i.e., liquid or ice). Knowledge of cloud phase is essential for specifying the optical properties of clouds, or else, large errors can be introduced in the calculation of the cloud radiative fluxes. Current parameterizations of cloud water partition in liquid and ice based on temperature are characterized by large uncertainty (Curry et al., 1996; Hobbs and Rangno, 1998; Intriery et al., 2002). This is particularly important in high geographical latitudes and temperature ranges where both liquid droplets and ice crystal phases can exist (mixed-phase cloud). The mixture of phases has a large effect on cloud radiative properties, and the parameterization of mixed-phase clouds has a large impact on climate simulations (e.g., Gregory and Morris, 1996). Furthermore, the presence of both ice and liquid affects the macroscopic properties of clouds, including their propensity to precipitate. Despite their importance, mixed-phase clouds are severely understudied compared to the arguably simpler single-phase clouds. In-situ measurements in mixed-phase clouds are hindered due to aircraft icing, difficulties distinguishing hydrometeor phase, and discrepancies in methods for deriving physical quantities (Wendisch et al. 1996, Lawson et al. 2001). Satellite-based retrievals of cloud phase in high latitudes are often hindered by the highly reflecting ice-covered ground and persistent temperature inversions. From the ground, the retrieval of mixed-phase cloud properties has been the subject of extensive research over the past 20 years using polarization lidars (e.g., Sassen et al. 1990), dual radar wavelengths (e.g., Gosset and Sauvageot 1992; Sekelsky and McIntosh, 1996), and recently radar Doppler spectra (Shupe et al. 2004). Millimeter-wavelength radars have substantially improved our ability to observe non-precipitating clouds (Kollias et al., 2007) due to their excellent sensitivity that enables the detection of thin cloud layers and their ability to penetrate several non-precipitating cloud layers. However, in mixed-phase clouds conditions, the observed Doppler moments are dominated by the highly reflecting ice crystals and thus can not be used to identify the cloud phase. This limits our ability to identify the spatial distribution of cloud phase and our ability to identify the conditions under which mixed-phase clouds form
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