An optimised method for calculating the O<sup>+</sup>-O collision parameter from aeronomical measurements

1995 ◽  
Vol 13 (5) ◽  
pp. 541-550 ◽  
Author(s):  
C. J. Davis ◽  
A. D. Farmer ◽  
A. Aruliah
Keyword(s):  
Collision Frequency ◽  
Radar Data ◽  
Data Sets ◽  
High Latitudes ◽  
Plasma Parameters ◽  
Data Set ◽  
F Region ◽  
Fabry Perot ◽  
Meridional Winds ◽  
Vertical Winds

Abstract. A study has been made of the interaction between the thermosphere and the ionosphere at high latitudes, with particular regard to the value of the O+-O collision parameter. The European incoherent scatter radar (EISCAT) was used to make tristatic measurements of plasma parameters at F-region altitudes while simultaneous measurements of the neutral wind were made by a Fabry-Perot interferometer (FPI). The radar data were used to derive the meridional neutral winds in a way similar to that used by previous authors. The accuracy of this technique at high latitudes is reduced by the dynamic nature of the auroral ionosphere and the presence of significant vertical winds. The derived winds were compared with the meridional winds measured by the FPI. For each night, the value of the O+-O collision parameter which produced the best agreement between the two data sets was found. The precision of the collision frequency found in this way depends on the accuracy of the data. The statistical method was critically examined in an attempt to account for the variability in the data sets. This study revealed that systematic errors in the data, if unaccounted for by the analysis, have a tendency to increase the value of the derived collision frequency. Previous analyses did not weight each data set in order to account for the quality of the data; an improved method of analysis is suggested.

Bayesian Classifier for Sparsity-Promoting Feature Selection

2015 ◽  
Vol 29 (06) ◽  
pp. 1550022 ◽  
Author(s):  
Danlei Xu ◽  
Lan Du ◽  
Hongwei Liu ◽  
Penghui Wang
Keyword(s):  
Feature Selection ◽  
Synthetic Data ◽  
Original Data ◽  
Radar Data ◽  
Bayesian Classifier ◽  
Classification Model ◽  
Data Sets ◽  
Data Set ◽  
Classification Boundary ◽  
Nonlinear Mappings

A Bayesian classifier for sparsity-promoting feature selection is developed in this paper, where a set of nonlinear mappings for the original data is performed as a pre-processing step. The linear classification model with such mappings from the original input space to a nonlinear transformation space can not only construct the nonlinear classification boundary, but also realize the feature selection for the original data. A zero-mean Gaussian prior with Gamma precision and a finite approximation of Beta process prior are used to promote sparsity in the utilization of features and nonlinear mappings in our model, respectively. We derive the Variational Bayesian (VB) inference algorithm for the proposed linear classifier. Experimental results based on the synthetic data set, measured radar data set, high-dimensional gene expression data set, and several benchmark data sets demonstrate the aggressive and robust feature selection capability and comparable classification accuracy of our method comparing with some other existing classifiers.

scholarly journals Thermospheric winds and temperatures above Mawson, Antarctica, observed with an all-sky imaging, Fabry-Perot spectrometer

2009 ◽  
Vol 27 (5) ◽  
pp. 2225-2235 ◽  
Author(s):  
C. Anderson ◽  
M. Conde ◽  
P. Dyson ◽  
T. Davies ◽  
M. J. Kosch
Keyword(s):  
Large Scale ◽  
Atmospheric Model ◽  
Horizontal Wind ◽  
Data Set ◽  
Average Behavior ◽  
Wind Speeds ◽  
Zonal Winds ◽  
F Region ◽  
Fabry Perot ◽  
Thermospheric Winds

Abstract. A new all-sky imaging Fabry-Perot spectrometer has been installed at Mawson station (67°36' S, 62°52' E), Antarctica. This instrument is capable of recording independent spectra from many tens of locations across the sky simultaneously. Useful operation began in March 2007, with spectra recorded on a total of 186 nights. Initial analysis has focused on the large-scale daily and average behavior of winds and temperatures derived from observations of the 630.0 nm airglow line of atomic oxygen, originating from a broad layer centered around 240 km altitude, in the ionospheric F-region. The 1993 Horizontal Wind Model (HWM93), NRLMSISE-00 atmospheric model, and the Coupled Thermosphere/Ionosphere Plasmasphere (CTIP) model were used for comparison. During the geomagnetically quiet period studied, observed winds and temperatures were generally well modelled, although temperatures were consistently higher than NRLMSISE-00 predicted, by up to 100 K. CTIP temperatures better matched our data, particularly later in the night, but predicted zonal winds which were offset from those observed by 70–180 ms−1 westward. During periods of increased activity both winds and temperatures showed much greater variability over time-scales of less than an hour. For the active night presented here, a period of 45 min saw wind speeds decrease by around 180 ms−1, and temperatures increase by approximately 100 K. Active-period winds were poorly modelled by HWM93 and CTIP, although observed median temperatures were in better agreement with NRLMSISE-00 during such periods. Average behavior was found to be generally consistent with previous studies of thermospheric winds above Mawson. The collected data set was representative of quiet geomagnetic and solar conditions. Geographic eastward winds in the afternoon/evening generally continued until around local midnight, when winds turned equatorward. Geographic meridional and zonal winds in the afternoon were approximately 50 ms−1 weaker than expected from HWM93, as was the transition to equatorward flow around midnight. There was also a negligible geographic zonal component to the post-midnight wind where HWM93 predicted strong westward flow. Average temperatures between 19:00 and 04:00 local solar time were around 60 K higher than predicted by NRLMSISE-00.

scholarly journals Simultaneous 6300 Å airglow and radar observations of ionospheric irregularities and dynamics at the geomagnetic equator

2018 ◽  
Vol 36 (2) ◽  
pp. 473-487 ◽  
Author(s):  
Dustin A. Hickey ◽  
Carlos R. Martinis ◽  
Michael Mendillo ◽  
Jeffrey Baumgardner ◽  
Joei Wroten ◽  
...  
Keyword(s):  
Plasma Temperature ◽  
Radar Data ◽  
Ionospheric Irregularities ◽  
Group Separation ◽  
Plasma Parameters ◽  
Zonal Winds ◽  
Fabry Perot ◽  
Low Latitudes ◽  
Spread F ◽  
Plasma Depletions

Abstract. In March 2014 an all-sky imager (ASI) was installed at the Jicamarca Radio Observatory (11.95∘ S, 76.87∘ W; 0.3∘ S MLAT). We present results of equatorial spread F (ESF) characteristics observed at Jicamarca and at low latitudes. Optical 6300 and 7774 Å airglow observations from the Jicamarca ASI are compared with other collocated instruments and with ASIs at El Leoncito, Argentina (31.8∘ S, 69.3∘ W; 19.8∘ S MLAT), and Villa de Leyva, Colombia (5.6∘ N, 73.52∘ W; 16.4∘ N MLAT). We use Jicamarca radar data, in incoherent and coherent modes, to obtain plasma parameters and detect echoes from irregularities. We find that ESF depletions tend to appear in groups with a group-to-group separation around 400–500 km and within-group separation around 50–100 km. We combine data from the three ASIs to investigate the conditions at Jicamarca that could lead to the development of high-altitude, or topside, plumes. We compare zonal winds, obtained from a Fabry–Pérot interferometer, with plasma drifts inferred from the zonal motion of plasma depletions. In addition to the ESF studies we also investigate the midnight temperature maximum and its effects at higher latitudes, visible as a brightness wave at El Leoncito. The ASI at Jicamarca along with collocated and low-latitude instruments provide a clear two-dimensional view of spatial and temporal evolution of ionospheric phenomena at equatorial and low latitudes that helps to explain the dynamics and evolution of equatorial ionospheric/thermospheric processes. Keywords. Ionosphere (equatorial ionosphere; ionospheric irregularities; plasma temperature and density)

scholarly journals Entropy Metrics of Radar Signatures of Sea Surface Scattering for Distinguishing Targets

2021 ◽  
Vol 13 (19) ◽  
pp. 3950
Author(s):  
Rui Jiang ◽  
Li-Na Li ◽  
Qiang Sun ◽  
Si-Zhang Hong ◽  
Jian-Jie Gao ◽  
...  
Keyword(s):  
Large Scale ◽  
Radar Data ◽  
Sample Entropy ◽  
Data Sets ◽  
Sea Clutter ◽  
Primary Target ◽  
Data Set ◽  
Wind Speeds ◽  
Scale Factors ◽  
Complexity Index

This paper analyzes sea clutter by a random series without assuming the scattering being independent. We quantitated the complexity of sea clutter by applying multiscale sample entropy. We found that above certain wave heights or wind speeds, and for HH or VV polarization, the target can be distinguished from sea clutter by regarding (i) the sample entropy at large scale factors or (ii) the complexity index (CI) as entropy metrics. This is because the backscattering amplitudes of range bins with the primary target were found equipped with the lowest sample entropy at large scale factors or the lowest CI compared to that of range bins with sea clutter only. To further cover low-to-moderate sea states, we constructed a polarized complexity index (PCI) based on the polarization signatures of the multiscale sample entropy of sea clutter. We demonstrated that the PCI is yet another alternative entropy metric and can achieve a superb performance on distinguishing targets within 1993’s IPIX radar data sets. In each data set, the range bins with the primary target turned to have the lowest PCI compared to that of range bins with sea clutter alone. Moreover, in our experiment using 1993’s IPIX radar data sets, the PCIs of range bins with sea clutter only were almost the same and stable in each data set, further suggesting that the proposed PCI metric can be applied in the presence of no or multiple targets through proper fitting curves.

scholarly journals 4-D-VAR assimilation of disdrometer data and radar spectral reflectivities for rain drop size distribution and vertical wind retrievals

2015 ◽  
Vol 8 (11) ◽  
pp. 12383-12431
Author(s):  
F. Mercier ◽  
A. Chazottes ◽  
L. Barthès ◽  
C. Mallet
Keyword(s):  
Data Assimilation ◽  
Size Distribution ◽  
Vertical Wind ◽  
Data Sets ◽  
Rain Event ◽  
Data Set ◽  
Light Rain ◽  
Break Up ◽  
Rain Events ◽  
Vertical Winds

Abstract. This paper presents a novel approach for retrieving the vertical raindrop size distribution (DSD) profiles and vertical winds during light rain events. It consists in coupling K band Doppler spectra and ground disdrometer measurements (raindrop fluxes) in a 2-D numerical model propagating the DSD from the clouds to the ground level. The coupling is made via a 4-D-VAR data assimilation algorithm. The model is, up to now, limited to the fall of droplets under gravity, modulated by the effects of vertical winds. Since evaporation, coalescence/break-up and horizontal air motion are not taken into account, we limit the study to light, stratiform rain events in which these phenomena appear negligible. We firstly use simulated data sets (data assimilation twin experiment) to show that the algorithm is able to retrieve the DSD profiles and vertical winds. It also demonstrates the ability of the algorithm to deal with the atmospheric turbulence (broadening of the Doppler spectra) and the instrumental noise. The method is then applied to a real case study which happened in the south-west of France during the autumn 2013. The data set collected during a long, quiet event (6 h duration, rain rate between 2 and 7 mm h−1) comes from an optical disdrometer and a 24 GHz vertically pointing Doppler radar. We show that the algorithm is able to explain the observations and supplies DSD and vertical wind profiles realistic compared to what could be expected for such a rain event. A perspective for this study is to apply it to extended data sets for a more thorough validation. Other data sets would also help to parameterize more phenomena needed in the model (evaporation, coalescence/break-up) to apply the algorithm to convective rain and to evaluate the adequacy of the model's parameterization.

Automatic detection of volcanic eruptions in Doppler radar observations using a neural network approach

2020 ◽  
Author(s):  
Matthias Hort ◽  
Daniel Uhle ◽  
Fabio Venegas ◽  
Lea Scharff ◽  
Jan Walda ◽  
...  
Keyword(s):  
Neural Network ◽  
Doppler Radar ◽  
Volcanic Eruptions ◽  
Radar Data ◽  
Visual Observation ◽  
Data Sets ◽  
Network Approach ◽  
Neural Network Approach ◽  
Data Set ◽  
The Impact

&lt;p&gt;Immediate detection of volcanic eruptions is essential when trying to mitigate the impact on the health of people living in the vicinity of a volcano or the impact on infrastructure and aviation. Eruption detection is most often done by either visual observation or the analysis of acoustic data. While visual observation is often difficult due to environmental conditions, infrasound data usually provide the onset of an event. Doppler radar data, admittedly not available for a lot of volcanoes, however, provide information on the dynamics of the eruption and the amount of material released. Eruptions can be easily detected in the data by visual analysis and here we present a neural network approach for the automatic detection of eruptions in Doppler radar data. We use data recorded at Colima volcano in Mexico in 2014/2015 and a data set recorded at Turrialba volcano between 2017 and 2019. In a first step we picked eruptions, rain and typical noise in both data sets, which were the used for training two networks (training data set) and testing the performance of the network using a separate test data set. The accuracy for classifying the different type of signals was between 95 and 98% for both data sets, which we consider quite successful. In case of the Turriabla data set eruptions were picked based on observations of OVSICORI data. When classifying the complete data set we have from Turriabla using the trained network, an additional 40 eruptions were found, which were not in the OVSICORI catalogue.&lt;/p&gt;&lt;p&gt;In most cases data from the instruments are transmitted to an observatory by radio, so the amount of data available is an issue. We therefore tested by what amount the data could be reduced to still be able to successfully detect an eruption. We also kept the network as small as possible to ideally run it on a small computer (e.g. a Rasberry Pi architecture) for eruption detection on site, so only the information that an eruption is detected needs to be transmitted.&lt;/p&gt;

scholarly journals RADOLAN_API: An Hourly Soil Moisture Data Set Based on Weather Radar, Soil Properties and Reanalysis Temperature Data

2021 ◽  
Vol 13 (9) ◽  
pp. 1712
Author(s):  
Thomas Ramsauer ◽  
Thomas Weiß ◽  
Alexander Löw ◽  
Philip Marzahn
Keyword(s):  
Soil Moisture ◽  
Weather Radar ◽  
Energy System ◽  
Radar Data ◽  
Data Sets ◽  
Data Set ◽  
Antecedent Precipitation ◽  
Main Driver ◽  
Terrestrial Water

Soil moisture is a key variable in the terrestrial water and energy system. This study presents an hourly index that provides soil moisture estimates on a high spatial and temporal resolution (1 km × 1 km). The long established Antecedent Precipitation Index (API) is extended with soil characteristic and temperature dependent loss functions. The Soilgrids and ERA5 data sets are used to provide the controlling variables. Precipitation as main driver is provided by the German weather radar data set RADOLAN. Empiric variables in the equations are fitted in a optimization effort using 23 in-situ soil moisture measurement stations from the Terrestial Environmental Observatories (TERENO) and a separately conducted field campaign. The volumetric soil moisture estimation results show error values of 3.45 Vol% mean ubRMSD between RADOLAN_API and station data with a high temporal accordance especially of soil moisture upsurge. Further potential of the improved API algorithm is shown with a per-station calibration of applied empirical variables. In addition, the RADOLAN_API data set was spatially compared to the ESA CCI soil moisture product where it altogether demonstrates good agreement. The resulting data set is provided as open access data.

scholarly journals Radio-echo sounding measurements and ice-core synchronization at Dome C, Antarctica

2016 ◽  
Author(s):  
Anna Winter ◽  
Daniel Steinhage ◽  
Emily J. Arnold ◽  
Donald D. Blankenship ◽  
Marie G. P. Cavitte ◽  
...  
Keyword(s):  
Ice Core ◽  
Basal Layer ◽  
Radar Data ◽  
Data Sets ◽  
Data Set ◽  
Range Resolution ◽  
Radio Echo Sounding ◽  
Sensitivity Studies ◽  
The Individual ◽  
Echo Sounding

Abstract. We present a compilation of radio-echo sounding (RES) measurements of five radar systems (AWI, BAS, CReSIS, INGV and UTIG) around the EPICA Dome C (EDC) drill site, East Antarctica. The aim of our study is to investigate the differences of the various systems in their resolution of internal reflection horizons (IRHs) and bedrock topography, penetration depth, and quality of imaging the basal layer. We address the questions of the compatibility of existing radar data for common interpretation, and the suitability of the individual systems for Oldest Ice reconnaissance surveys. We find that the most distinct IRHs and IRH patterns can be identified and transferred between most data sets. Considerable differences between the RES systems exist in range resolution and depiction of the basal layer. Considering both aspects, which we judge as crucial factors in the search for old ice, the CReSIS and the UTIG systems are the most valuable ones. In addition to the RES data set comparison we calculate a synthetic radar trace from EDC density and conductivity profiles. We identify ten common IRHs in the measured RES data and the synthetic trace. The reflection-causing conductivity sections are determined by sensitivity studies with the synthetic trace. In this way, we accomplish an accurate two-way travel time to depth conversion for the reflectors, without having to use a precise velocity-depth function that would accumulate depth uncertainties with increasing depth. The identified IRHs are assigned with the AICC2012 time scale age. Due to the isochronous character of these conductivity-caused IRHs, they are a means to extend the Dome C age structure by tracing the IRHs along the RES profiles.

The social wasp Vespula germanica (Fabricius) (Hymenoptera: Vespidae) population dynamics in England over 39 years.

2018 ◽  
Vol 154 (2) ◽  
pp. 149-155
Author(s):  
Michael Archer
Keyword(s):  
Population Dynamics ◽  
Population Dynamic ◽  
Ecological Factors ◽  
Social Wasp ◽  
Data Sets ◽  
Data Set ◽  
Vespula Germanica ◽  
The Social ◽  
Minimum Number ◽  
Suction Traps

1. Yearly records of worker Vespula germanica (Fabricius) taken in suction traps at Silwood Park (28 years) and at Rothamsted Research (39 years) are examined. 2. Using the autocorrelation function (ACF), a significant negative 1-year lag followed by a lesser non-significant positive 2-year lag was found in all, or parts of, each data set, indicating an underlying population dynamic of a 2-year cycle with a damped waveform. 3. The minimum number of years before the 2-year cycle with damped waveform was shown varied between 17 and 26, or was not found in some data sets. 4. Ecological factors delaying or preventing the occurrence of the 2-year cycle are considered.

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