The Experts below are selected from a list of 11781 Experts worldwide ranked by ideXlab platform

Jonathan Whale - One of the best experts on this subject based on the ideXlab platform.

  • us military airspace and Meteorological Radar system impacts from utility class wind turbines implications for renewable energy targets and the wind industry
    Renewable Energy, 2013
    Co-Authors: T Auld, M P Mchenry, Jonathan Whale
    Abstract:

    A substantial number of wind energy projects have been stalled or abandoned in the United States of America (US) due to concerns over the effects of wind turbines on Radar installations. Between 2008 and 2010, military, airspace, or Meteorological Radar concerns in the US contributed to the delay or abandonment of an estimated 20,000 MW of wind energy capacity. These delays are a likely major factor influencing the current US Administration's failure to double non-hydro renewable generation from 2008 to 2011; a target stated by the US President in a joint session address to Congress in February 2009. The delays are also a threat to the US Department of Energy's target to produce 20% of electricity from wind energy by 2030 – unless Radar-related barriers are mitigated. This work includes interviews with two senior representatives, from the US Department of Defence (DOD) and the American Wind Energy Association (AWEA), discussing the nature of concerns pertaining to the effects of wind turbines on Radar and military/aviation in the US alongside approaches that have been trialled that aim to resolve such concerns. This research finds that the Energy Siting Clearing House, established within the DOD to review delayed wind farm projects, has brought much needed coordination to the approval process. A key challenge for any review body, however, will be to deliver an objective outcome that is not overturned by alternative political agendas. Integral to the success of any approach will be a sufficient capacity and mandate to facilitate the technical and non-technical cross-disciplinary and interagency research generating a balance between military, airspace, Meteorological, and wind energy industry/political objectives.

Efrat Morin - One of the best experts on this subject based on the ideXlab platform.

  • using trmm spaceborne Radar as a reference for compensating ground based Radar range degradation methodology verification based on rain gauges in israel
    Journal of Geophysical Research, 2011
    Co-Authors: Marco Gabella, Efrat Morin, Riccardo Notarpietro
    Abstract:

    [1] While intense scientific efforts have focused on Radar precipitation estimation in temperate climatic regimes, relatively few studies have examined dry climatic regions. This paper examines rain depth estimation for a 19 day rainfall period in Israel, where the gauge spatial distribution is particularly nonhomogeneous. This fact exacerbates the main drawback of rain gauge observations, which is undersampling. Meteorological ground-based Radar (GR) can supplement the desired information on precipitation distribution. However, especially in a complex orographic region, Radar scientists are faced with beam broadening with distance, nonhomogeneous beam filling, and partial-beam occultation, together with changes in the vertical reflectivity profile. This paper presents an improvement of GR precipitation estimates thanks to a range adjustment based on spaceborne Meteorological Radar. In the past, the Tropical Rainfall Measuring Mission (TRMM) satellite Radar was used for checking the GR mean field bias around the world. To our knowledge, however, it is the first time that GR-derived cumulative rainfall amounts show a better agreement with gauges, thanks to the mean field bias and range-dependent compensation derived using the well-calibrated Ku band TRMM Radar as a reference. The average bias improves from +1.0 dB to −0.3 dB; more interesting and difficult to obtain is a reduction of the dispersion of the error. Using TRMM-based range compensation, the scatter decreases from 2.21 dB to 1.93 dB. We conclude that it is well worth trying to compensate for the GR range degradation.

  • estimating rainfall intensities from weather Radar data the scale dependency problem
    Journal of Hydrometeorology, 2003
    Co-Authors: Efrat Morin, Witold F Krajewski, David C Goodrich, Soroosh Sorooshian
    Abstract:

    Meteorological Radar is a remote sensing system that provides rainfall estimations at high spatial and temporal resolutions. The Radar-based rainfall intensities ( R) are calculated from the observed Radar reflectivities ( Z). Often, rain gauge rainfall observations are used in combination with the Radar data to find the optimal parameters in the Z‐R transformation equation. The scale dependency of the power-law Z‐R parameters when estimated from Radar reflectivity and rain gauge intensity data is explored herein. The multiplicative ( a) and exponent (b) parameters are said to be ‘‘scale dependent’’ if applying the observed and calculated rainfall intensities to objective function at different scale results in different ‘‘optimal’’ parameters. Radar and gauge data were analyzed from convective storms over a midsize, semiarid, and well-equipped watershed. Using the root-mean-square difference (rmsd) objective function, a significant scale dependency was observed. Increased time- and space scales resulted in a considerable increase of the a parameter and decrease of the b parameter. Two sources of uncertainties related to scale dependency were examined: 1) observational uncertainties, which were studied both experimentally and with simplified models that allow representation of observation errors; and 2) model uncertainties. It was found that observational errors are mainly (but not only) associated with positive bias of the b parameter that is reduced with integration, at least for small scales. Model errors also result in scale dependency, but the trend is less systematic, as in the case of observational errors. It is concluded that identification of optimal scale for Z‐R relationship determination requires further knowledge of reflectivity and rainintensity error structure.

C G Collier - One of the best experts on this subject based on the ideXlab platform.

  • fuzzy logic filtering of Radar reflectivity to remove non Meteorological echoes using dual polarization Radar moments
    Atmospheric Measurement Techniques, 2015
    Co-Authors: David Dufton, C G Collier
    Abstract:

    Abstract. The ability of a fuzzy logic classifier to dynamically identify non-Meteorological Radar echoes is demonstrated using data from the National Centre for Atmospheric Science dual polarisation, Doppler, X-band mobile Radar. Dynamic filtering of Radar echoes is required due to the variable presence of spurious targets, which can include insects, ground clutter and background noise. The fuzzy logic classifier described here uses novel multi-vertex membership functions which allow a range of distributions to be incorporated into the final decision. These membership functions are derived using empirical observations, from a subset of the available Radar data. The classifier incorporates a threshold of certainty (25 % of the total possible membership score) into the final fractional defuzzification to improve the reliability of the results. It is shown that the addition of linear texture fields, specifically the texture of the cross-correlation coefficient, differential phase shift and differential reflectivity, to the classifier along with standard dual polarisation Radar moments enhances the ability of the fuzzy classifier to identify multiple features. Examples from the Convective Precipitation Experiment (COPE) show the ability of the filter to identify insects (18 August 2013) and ground clutter in the presence of precipitation (17 August 2013). Medium-duration rainfall accumulations across the whole of the COPE campaign show the benefit of applying the filter prior to making quantitative precipitation estimates. A second deployment at a second field site (Burn Airfield, 6 October 2014) shows the applicability of the method to multiple locations, with small echo features, including power lines and cooling towers, being successfully identified by the classifier without modification of the membership functions from the previous deployment. The fuzzy logic filter described can also be run in near real time, with a delay of less than 1 min, allowing its use on future field campaigns.

Volodymyr Polishchuk - One of the best experts on this subject based on the ideXlab platform.

  • monitoring of low level wind shear by ground based 3d lidar for increased flight safety protection of human lives and health
    International Journal of Environmental Research and Public Health, 2019
    Co-Authors: Pavol Nechaj, Ladislav Gaal, Juraj Bartok, Olga Vorobyeva, Martin Gera, Miroslav Kelemen, Volodymyr Polishchuk
    Abstract:

    Low-level wind shear, i.e., sudden changes in wind speed and/or wind direction up to altitudes of 1600 ft (500 m) above-ground is a hazardous Meteorological phenomenon in aviation. It may radically change the aerodynamic circumstances of the flight, particularly during landing and take-off and consequently, it may threaten human lives and the health of passengers, people at the airport and its surrounding areas. The Bratislava Airport, the site of this case study, is one of the few airports worldwide and the first in Central Europe that is equipped with a Doppler lidar system, a perspective remote sensing tool for detecting low-level wind shear. The main objective of this paper was to assess the weather events collected over a period of one year with the occurrences of low-level wind shear situations, such as vertical discontinuities in the wind field, frontal passages and gust fronts to increase the level of flight safety and protect human lives and health. The lidar data were processed by a computer algorithm with the main focus on potential wind shear alerts and microburst alerts, guided by the recommendations of the International Civil Aviation Organisation. In parallel, the selected weather events were analyzed by the nearby located Meteorological Radar to utilize the strengths of both approaches. Additionally, an evaluation of the lidar capability to scan dynamics of aerosol content above the airport is presented.

F J Yanovsky - One of the best experts on this subject based on the ideXlab platform.