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frequency response. This calculation gives the curves of Figure 3 for two of the B 6 - values ofFigure 2. It shows that higher resolution requires a larger bandwidth. In this case the -6 dBbandwidth for a 500 m pulse (B 6 -=1.04) is 240 kHz, while for the B 6 -=0.55 case, the -6 dBbandwidth is only 152 kHz.Figure 3. Frequency response of system using 500 m long pulse, with two differentB6- products. The box shows the -6 dB points of the matched filter.The Nyquist criterion states that if we want to be able to fully reconstruct this signal, weneed to sample at a rate at least twice the highest frequency in the signal. The choice of themaximum frequency is arbitrary so if one uses the -6 dB frequencies, then this means that thesampling needs to be done at 2*240 kHz, or 480 kHz, or once every 2.1 s (312.5 m). Note thatmany times in the radar community, sampling in range at intervals less than one pulse length isreferred to as “over-sampling”. Many meteorological radars set the sampling equal to the pulselength so that the samples are independent. However, if one uses a Nyquist criterion to determinesample spacing with the goal of accurately reproducing the signal as a function of time, or theprofile as a function of range, then it would not be unreasonable to use 2 or more samples perpulse length.When looking at time series from a single height, it is useful to examine the Dopplerspectrum of the time series. This spectral representation shows how the signal varies asfrequency, or the reciprocal of time. This is the method used by the AL to obtain the wind speedsat each height in order to produce the data in Figure 1. Another time series available from theradar is the range series, showing the atmospheric profile of the received signal. We usuallyconvert the time delay from the radar to the echoing volume to distance from the radar, but it isstill a time series. In a manner analogous to time series spectra, a spatial frequency could bedefined, as the reciprocal of range instead of time. Here we choose not to do this, but to discussspatial frequencies in units of reciprocal length. For example, the 3.3 s long pulse requires a 240kHz bandwidth between the -6 dB points. The reciprocal of 240 kHz is 4.17 s, which has areciprocal scale length of 625 m. This means that spatial features of 625 m or shorter (higherfrequencies) have been attenuated in the signal by more than 0.25 (-6 dB). If we look at the sameatmosphere with a B 6 -=0.55 and a 500 m long pulse, the reciprocal scale length is 987 m,reflecting the fact that the receive bandwidth is narrower.The time and frequency domains tell us similar information. In the time domain, wherethe system response is specified by the resolution, we learn about the ranges that contribute tothe data in a sample. In the frequency domain, the reciprocal lengths define the size of thestructures that contribute to the data at a given range. The frequency domain also gives usinformation about how we need to sample our data in range in order to accurately reproduce thedata.Why do we want to be able to accurately reconstruct the range profile of the radar signal?The simple answer is to improve the accuracy and precision of the instrument. If we want to264
place features in the profile with more precision than ½ of the range resolution we need to be ableto reconstruct the profile. If we want to be able to report our data at standard heights, insteadof heights determined by the radar hardware, we need to be able to interpolate the data.Interpolation is a reconstruction of the signal followed by re-sampling at the desired ranges. Ifwe want to be able to follow signal attributes in range, we need to make sure we have an accuraterange representation of the signal.In Figure 1, the data were obtained using matched filters (B 6 -=1.04) in all three pulselengths. The range resolutions of the system bandwidths are 115 m for the 100-m long pulse, 574m for the 500-m pulse, and 1148 m for the 1000-m pulse. The 1000-m and 500-m data aresampled twice per pulse length, and the 100-m data are sampled once per pulse length. Figure4 shows part of the data from Figure 1. The range resolution of each mode has been shown asvertical bars at two heights for each profile, so that the volume represented by each sample isclearer. The different attenuation of spatial scales is apparent. The magnitude of the low-leveljet is smaller with the longer pulse lengths, as expected, but is not the simple average of theappropriate number of points. For example, the average of the 5 largest, contiguous speeds ofthe 100-m data is 11.4 ms -1 , which is still much larger than the 10.6 ms -1 observed by the 500-mpulse. The differences in spatial averaging by the different pulse lengths do not account for allof the observed differences in the profiles. Future work will be directed towards studying thepossible interactions between atmospheric reflectivity and velocity structures and the rangeresolutioncharacteristics of various profilers.Figure 4. Details of the mean February wind speed for 1994-1996 at ChristmasIsland, Kiribati. The vertical bars indicate the range resolution of the different pulselengths.Range resolution and data sampling are complex issues. The reflectivity of theatmosphere interacts with the radar in a non-linear fashion to produce results that are notstraightforward. When we are interesting in the changes of the signal with range, i.e. profiling,special attention needs to be made to the spacing between the samples in range. Careful attentionto these issues is important to help produce better interpretations of the data.REFERENCES:Doviak, R.J., and D.S. ZrniA, Doppler Radar and Weather Observations, Second Edition.Academic Press, 562pp, 1993.Johnston, P.E., L.M. Hartten, C.H. Love, D.A. Carter, and K.S. Gage, Range errors in windprofiling caused by strong reflectivity gradients, Journal of Atmospheric and OceanicTechnology, 19, 934-953, 2002.265
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MST10Tenth InternationalWORKSHOPOn
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MST 10 Group PictureMay 15 th , 200
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TENTH INTERNATIONAL WORKSHOP ON TEC
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Table of ContentsPREFACE ..........
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I.2.18 FURTHER OBSERVATIONS OF PMSE
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I.3.27 NEW MST RADAR METHODS FOR ME
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I.4.19 STUDY OF A MESOSCALE LAND-TO
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I.5.502 AN ATTEMPT TO CALIBRATE THE
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PrefaceMST10The Tenth International
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and the local organizing committee,
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The operational aspects and recent
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To improve the understanding of dyn
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Improving MST radar resolution by u
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latitudes, arguing that the former
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Report on Session I.3 “Winds, Wav
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Turbulence.The session then moved i
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Report on Session I.4 “Meteorolog
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Multiple Antenna Profiling Radar (M
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Report on Session II “Novel Persp
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synchronized by GPS and connected v
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The highly positive response of the
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10th International Workshop on Tech
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10th International Workshop on Tech
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Session I.1: Radar scattering proce
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⎡7800 ∂q⎤(3)⎢ 15500q⎥M =
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Figure 2 compares profiles of ω B
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Figure 1: Data from the MST radar a
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Ri =shear2ωB22⎛ ∂u⎞ ⎛ ∂v
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Meridional (deg)1050−5−10Echo P
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Subarray Configuration, Capon Metho
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Fig. 2 PMSE plot (SOUSY Svalbard Ra
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VHF radar interferometry had shown
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turbulence. From Figures 1 and 2, i
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SummaryFrom the aspect sensitivity
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a specific range. In this work, syn
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P C(dB)(a) Echo Power60504030200.70
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most occidental area of South Ameri
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Quegan, 1992). It should be useful
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measurements, is shown in figure 1(
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The present observations thus empha
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RECENT OBSERVATIONS OF E REGION FIE
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measured spectra in order to separa
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drifts at E and F regions heights b
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• Are characterized by type II ec
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The main parameters that could be o
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THE ROLE OF UNSTABLE SPORADIC-E LAY
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(σ H / σ P )E y (where σ H and
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STUDY OF A LOW E-REGION QUASI-PERIO
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100 m/syrFigure 4: Geometry of the
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Where the notations carry same mean
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Where dx/dt and dy/dt are the veloc
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non-negativity of the image is prio
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spectrum corresponding to the backs
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The Artigas and Machu-Picchu Statio
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Arguments against the second altern
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Extension of the Kolmogorov spectru
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volumeESRvolumeSSRSSR SSRESR ESRSSR
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individual particles in a statistic
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Anomalous spectraTalkner [4] studie
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To observe the E region FAI echoes,
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matter daytime or nighttime and are
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two sub-arrays, each sub-array made
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4. SummaryHere we describe a radio
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Figure 1. E-region DPS4 spectra, ri
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effects. It is therefore plausible
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1996 and high in 2002). The electri
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electric fields map along the geoma
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SNR condition is always difficult a
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Figure-4 Power spectrum plots of a
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As we show below, Jicamarca offers
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particularly during daytime counter
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where ˆδ nm = (δ l − δ m )
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PMSE is more easily interpreted as
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ResultsTemperature climatology• s
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Simultaneous PMSE and NLC observati
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ResultsSeasonal variationMSE are no
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Figure 2: MSE parameters as functio
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Session I.3: Winds, waves and turbu
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poor. It was shown that poor perfor
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The use of diffraction pattern simi
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F 13 (ξ x ′) = (1 − cos 2ψ N)
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Figure 3: (a) Baseline length depen
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3. ResultsFigure 1 shows the amplit
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variability.Figure 4 shows the aver
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Figure 1. Period-time amplitude wav
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the 12-h and 24-h periodicities in
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winds and variances at altitudes 70
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similar correlation with larger mag
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of the refraction index are not equ
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Fig. 8. Zonal wind (top) and temper
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STUDIES ON ATMOSPHERIC GRAVITY WAVE
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1100-1200 hours. From this plot 6.3
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STUDIES ON WINDS AND MOMENTUM FLUXE
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3.4 Monthly variation of momentum f
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DEEP PENETRATIVE CONVECTION AND GEN
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ly changes direction with time with
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189
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191
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193
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These two last relations are the on
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3.2.1 From v ′2 to ɛ kThe questi
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5.2 Frequency distributionsSeveral
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ReferencesAlisse J.-R. and C. Sidi.
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Röttger J. and C.H. Liu. Partial r
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Specular reflection is negligible f
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−0.5C n2 Distribution (PROUST & S
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the beamwidth, α is the zenith ang
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this latitude in late April). Surfa
Page 219 and 220: Fig. 1. Median (upper) winds and (l
Page 221 and 222: Fig.1. Lines of constant radial vel
Page 223 and 224: which have not yet been considered
Page 225 and 226: is calculated from the radiosonde t
Page 227 and 228: Figure 3: Time-altitude cross-secti
Page 229 and 230: Absorption of cosmic noise is cause
Page 231 and 232: Incoherent scatter spectracompared
Page 233 and 234: variations of spectral widths, refr
Page 235 and 236: Figure 1. Diurnal variation of Turb
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Page 243 and 244: The main recently assumed mechanism
Page 245 and 246: Figure 2. Statistics of numbers of
Page 247 and 248: LIDAR OBSERVATIONS OF MIDDLE ATMOSP
Page 249 and 250: latitudinal dependence of the seaso
Page 251 and 252: APPLICATION OF THE DUAL-BEAMWIDTH M
Page 253 and 254: Figure 2: Mean zonal and meridional
Page 255 and 256: JLKLLK/ILIL6II/G/II/G/LEODFLK/LO/DD
Page 257 and 258: The monthly diurnal mean of horizon
Page 259 and 260: Session I.4: Meteorological Phenome
Page 261 and 262: Integration of the VHF wind profile
Page 263 and 264: Figure 1 : Map of the Lago Maggiore
Page 265 and 266: precipitating clouds, the cyclonic
Page 267 and 268: Eyewall(a)(b)(c)(d)Fig. 3: Radius-h
Page 269: as low as 0.55. The Piura 50-MHz ra
Page 273 and 274: • Period 1 (June 1-10): SCCs exis
Page 275 and 276: Sumatera occurs by stratiform cloud
Page 277 and 278: very interesting to note the double
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Page 281 and 282: Typhoon LekimaFig. 2 Typhoon Lekima
Page 283 and 284: Fig. 5 Passage of typhoon Hayan on
Page 285 and 286: the 50 cm 2 sensor head, enabling t
Page 287 and 288: 22 June 2000 23:22:23 - 23:24:20 at
Page 289 and 290: the time-height section of a convec
Page 291 and 292: Thurai, M., T.Iguchi,T. Kozu, J.D.E
Page 293 and 294: There are two main mechanisms which
Page 295 and 296: Horel, J.D. and Cornejo-Garrido, A.
Page 297 and 298: estimating two independent and redu
Page 299 and 300: RASS THETA (K) RASS v-component (m/
Page 301 and 302: Surface winds usually range from 10
Page 303 and 304: weak (maximum of 5 m s -1 ) and the
Page 305 and 306: The vertical component from the VTB
Page 307 and 308: Figure 8 shows the profile of virtu
Page 309 and 310: 2 3D ( , ) ( ) ( ) ˆ ( ) ˆp∆ xm
Page 311 and 312: presented in Praskovsky et al. (200
Page 313 and 314: In Fig. 2 a sketch of a mountain le
Page 315 and 316: In Fig. 8 the lamina is aligned on
Page 317 and 318: Figure 1: composite day (13 days) o
Page 319 and 320: virtual sensible heat fluxes ( Wm-2
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3. Characteristics of precipitation
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Fig. 3: Horizontal distribution of
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3. Results and discussionUHF profil
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Figure 4. Monthly variation of slop
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system with two receiving antennae,
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cycle of precipitation. Figure 3(a)
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Histogram of Zonal Velocityh=5.13 K
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5. Summary of results and concludin
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the two nearby major cities, Chenna
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Boundary layer height, km32.521.5(a
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Figure 1:Data from the MST radar at
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spectral processing. In this partic
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3. Results and discussionIn the pre
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4. SummaryAn attempt has been made
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The purpose of this study is to exa
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Figure1. Three-day average of momen
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3. The improved method to estimate
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But in case of period until 1800 UT
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Session I.5: Operational Aspects an
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The profilers of WINDAS weredesigne
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NOAA, 1994 : Wind profiler assessme
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FIRST RESULTS OF THE BOUNDARY LAYER
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Figure 3. Pulse Design Diagram to s
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MOVEABLE UHF/S-BAND PROFILER/DISDRO
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one-minute Z values determined from
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TOWARD A MULTISENSOR GROUND BASED R
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3. Cloud Evolution Case StudyOn the
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DEVELOPMENT OF A DIGITAL RECEIVER F
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Experiment 1 Experiment 2IPP 999Km
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ELECTRONIC DIGITAL BEAMFORMING IMPL
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The main element of the unit (figur
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.ON-LINE ADAPTIVE DC-GROUND-CLUTTER
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esulting in a widening of the bandw
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ON THE RADIATION EFFICIENCY OF COCO
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Table 2: Experiment #1 results, Tra
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A NEW NARROW BEAM MF RADAR AT 3 MHZ
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Off-zenith beams towards N, S, E, W
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95ALWIN VHF radar: signal powerdB80
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ANTENNA BEAM VERIFICATION USING COS
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Figure 2: A 45 MHz reference sky te
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AN ATTEMPT TO CALIBRATE THE UHF STR
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is at 4.7 km, but in the first 4-ga
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QUALITY CONTROL FOR DOPPLER WIND PR
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The resulting moments are subjected
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SOUSY RADAR AT JICAMARCA: SYSTEM DE
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NEControl andcomputer roomCompCoute
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THE EQUATORIAL ATMOSPHERE RADAR:SYS
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Table 1: Specifications of the EAR
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VHF ATMOSPHERIC AND METEOR RADAR IN
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ased upon a geotechnical engineerin
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VORTICAL MOTIONS OBSERVED WITH THE
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interpolation from the original gri
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A NEW MINIRADAR TO INVESTIGATE URBA
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e eliminated to analyze correctly t
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Session PWG 1: System Calibrations
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Session PWG 2: Data Analysis, Valid
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• the time series vectors x(k) of
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Fig. 4: reflectivity of the hydrome
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Session PWG 3: Accuracies and Requi
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Session PWG 4: International Collab
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Session II.E: NOVEL PERSPECTIVES AN
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2 Proposed AlgorithmReceived signal
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N#4E-1-16E1A1#1#2A-1-1C1#3C-1-19Fig
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of conventional DCMP, with which th
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applying the directional constraint
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while for a beam of finite width, t
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In order to make the process more q
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WHAT IS TURBULENCE SEEN BY VHF RADA
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Enhanced resolution applyingpulse s
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Beckmann, Spizichino, 1964Fig. 8 Po
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Fig. 11 Plots of temporal variation
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Fig. 14 Distributions of phase cent
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Hocking, W.K., Radar studies of sma
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THE STRUCTURE FUNCTION-BASED APPROA
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{ Ui( t), Vi( t), Wi( t)} = { Ui ,
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161). Assumption 2H: the instantane
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Only the second order SF are consid
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fluctuations umk( t ) along the bas
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VHF PARASITIC RADAR INTERFEROMETRYF
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• All the costs of transmitter pr
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Figure 2: Example of range-azimuth
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Target Altitude, km1009080706050403
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ReferencesGriffiths, H. D., A. J. G
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Participants ListAvery, James P.Uni
Page 489 and 490:
Hysell, David L.EAS/Cornell Univers
Page 491 and 492:
Silva, Robert R.ATRADAustraliarsilv
Page 493 and 494:
AAdachi, A. .......................
Page 495:
TTabary, P. .......................
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