1,721,004 research outputs found
Rain field and reflectivity vertical profile reconstruction from C-band radar volumetric data
No full textOperating a meteorological radar is generally a challenging task when in presence of a significant beam blockage as in complex orography. Apart from enhanced ground clutter, mountainous obstructions of the radar beam can significantly reduce the radar visibility and, thus, its monitoring capabilities. Self-consistent adaptive techniques to reconstruct vertical profiles of reflectivity (VPR) and near-surface rain-rate fields from high-elevation reflectivity bins are here proposed, compared, and tested for ranges up to 60 km. The methodology is based on statistical estimators trained by a large reflectivity volumetric datasets, classified into stratiform and convective rain regimes and resampled onto a uniform Cartesian grid by means of a modified Cressman technique. For what concerns reflectivity vertical profiles, two methods, respectively named statistical nonlinear reconstruction (NSR) and neural network reconstruction (NNR), are considered. The NSR method is based on the principal component analysis, applied to the radar dataset, in order to extract significant reflectivity-profile variance. A retrieval technique, based on a nonlinear multiple regression scheme, is then used to infer near-surface reflectivity from available high-altitude echoes at a given range. The NNR is based on a three-layer artificial neural network trained by means a feedforward backpropagation algorithm. For what concerns the near-surface rain retrieval, besides a power-law reflectivity-rain-rate (ZR) approach, a three-layer neural network technique is also set up in order to estimate surface rain rate from reconstructed VPR. The proposed reconstruction techniques are here illustrated by using volumetric data acquired by the C-band Doppler single-polarization radar, operated in L’Aquila, Italy. A case study, related to a rainfall event that occurred during fall 2000, is discussed. Using a test area within 60 km from the radar site and simulating the presence of beam obstructions, a comparison of NSR and NNR with conventional area average reconstruction techniques shows that the percentage improvement of both NSR and NNR approaches is significant, both for the error bias (by 30% to more than 50%, depending on altitude) and variance (by 10% to more than 20%). A sensitivity test indicates that the VPR reconstruction procedure is fairly robust to missing data, especially in terms of error bias. The comparison of estimated radar rainfall with rain gauge data measurement is also illustrated. The mean field bias closer to its optimal value and an error variance much smaller is obtained when neural network techniques are applied than with conventional ZR methods for both techniques of reconstruction. With respect to the latter, the obtained improvement is more than 40% in terms of root mean square error and is comparable when estimating near-surface rain rate using either NSR or NNR methods to reconstruct the reflectivity vertical profiles. Limitations, potential, and future developments of the proposed adaptive reconstruction techniques are finally discussed
Analysis and synthesis of rainfall time series using disdrometer data
No full textHydrometeorological and radio propagation applications
can benefit from the capability to model the time evolution of
raindrop size distribution (RSD). A new stochastic vector autoregressive
semi-Markov model is proposed to randomly synthesize
(generate) the temporal series of the three driving parameters of
a normalized Gamma RSD. Rainfall intermittence is reproduced
through a discrete semi-Markov process, modeled from disdrometer
measurements using two-state analytical statistics of rain and
dry period duration. The overall model is set up by means of a
large set of disdrometer measurements, collected from 2003 to
2005 at Chilbolton, U.K. The driving parameters of the retrieved
RSD are estimated using three approaches: the Gamma moment
method and the 1-D and 3-D maximum-likelihood methods. Interestingly,
these methodologies lead to quite different results,
particularly when one is interested in evaluating RSD higher order
moments such as the rain rate. The accuracy of the proposed RSD
time-series generation technique is evaluated against available
disdrometer measurements, providing excellent statistical scores
Supervised classification and estimation of hydrometeors using C-band dual-polarized radars: a Bayesian approach
No full textAbstract—In this paper, a Bayesian statistical approach for
supervised classification and estimation of hydrometeors, using
a C-band polarimetric radar, is presented and discussed. The
Bayesian Radar Algorithm for Hydrometeor Classification at
C-band (BRAHCC) is supervised by a backscattering microphysical
model, aimed at representing ten different hydrometeor classes
in water, ice, and mixed phase. The expected error budget is
evaluated by means of contingency tables on the basis of C-band
radar noisy and attenuated synthetic data. Its accuracy is better
than that obtained from a previously developed fuzzy logic C-band
classification algorithm. As a second step of the overall retrieval
algorithm, a multivariate regression is adopted to derive water
content statistical estimators, exploiting simulated polarimetric
radar data for each hydrometeor class. The BRAHCC methodology
is then applied to a convective hail event, observed by two
C-band dual-polarized radars in a network configuration. The
hydrometeor classification along the line of sight, connecting the
two C-band radars, is performed using the BRAHCC applied to
path-attenuation-corrected data. Qualitative results are consistent
with those derived from the fuzzy logic algorithm. Hydrometeor
water content temporal evolution is tracked along the radar line
of sight. Hail vertical occurrence is derived and compared with an
empirical hail detection index applied along the radar connection
line during the whole event
Inside Volcanic clouds: Remote Sensing of Ash Plumes Using Microwave Weather Radars
No full textAsh clouds due to volcanic eruptions can be detected in near–real time, quantitatively
retrieved, and microphysically characterized by using ground-based microwave weather
radars and their high-resolution spatial–temporal coverage.Ash clouds due to volcanic eruptions can be detected in near–real time, quantitatively
retrieved, and microphysically characterized by using ground-based microwave weather
radars and their high-resolution spatial–temporal coverage
Supervised fuzzy-logic classification of hydrometeors using C-band dual-polarized radars
No full textA model-based fuzzy-logic method for hydrometeor
classification using C-band polarimetric radar data is presented
and discussed. Membership functions of the fuzzy-logic algorithm
are designed for best fitting simulated radar signatures at
C-band. Such signatures are derived for ten supervised hydrometeor
classes by means of a fully polarimetric radar scattering
model. The Fuzzy-logic Radar Algorithm for Hydrometeor Classification
at C-band (FRAHCC) is designed to use a relatively
small set of polarimetric observables, i.e., copolar reflectivity and
differential reflectivity, but a version of the algorithm based on
the use of specific differential phase is also numerically tested and
documented. The classification methodology is applied to volume
data coming from a C-band two-radar network that is located in
north Italy within the Po valley. Numerical and experimental results
clearly show the improvements of hydrometeor classification,
which were obtained by using FRAHCC with respect to the direct
use of fuzzy-logic-based algorithms that are specifically tuned
for S-band radar data. Moreover, the availability of two C-band
rainfall observations of the same event allowed us to implement
a path-integrated attenuation correction procedure, based on
either a composite radar field approach or a network-constrained
variational algorithm. The impact of these correction procedures
on hydrometeor classification is qualitatively discussed within the
considered case study
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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