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The overall processing flow of the NIMA algorithm is shown in Figure 1. Some of the majorprocessing steps are illustrated in Figures 2-3 using an example spectrum from the northbeam of the Juneau Lemon Creek profiler containing ground clutter, RFI, and point targetcontaminants. Figure 2 shows the averaged spectra both as stacked spectra and as the spectralintensity contour over Doppler velocity (x) and range (y). Median filtering in velocity andrange mitigates the effects of point target contamination and smoothes the spectral surface tofacilitate mathematical analysis.Figure 2. Stacked spectra (left), equivalent spectral intensity contour with POP moments (center), and 2dmedian-filtered spectra (right) from Lemon Creek profiler.Spectral intensity scaling is used to emphasize different parts of the spectral surface. Usingrange-normalized scaling of the 2d median filtered values emphasizes the intensity contour inregions of low signal-to-noise (SNR). Mathematical analysis using equation (1) over a smallregion surrounding each point of the resulting spectral surfaces yields information about thelocal curvatures and gradients of the surface.2 2zxy ( , ) = ax ( − x0) + bx ( −x0)( y− y0) + cy ( − y0) + d( x− x0) + ey ( − y0)+ f (1)A number of these derived fields are calculated and membership maps are used to translateeach into a “Doppler Peak membership field.” Fuzzy logic is then used combine these into acombined Doppler Peak membership field. As illustrated in Figure 3, spectral regions withhigh Doppler peak membership values are grouped into “features” that can be classified aspotentially atmospheric, clutter, and/or RFI. The highest scoring atmospheric feature is usedto identify the spectral points from which to calculate the moments.400Figure 3. Combined Doppler Peak membership field (left), resulting Doppler peak features (center), andNIMA moments overlaid on the 1d (velocity) median-filtered spectra used to calculate the moments (right).Confidence in the moments is shown in the side plot.
The resulting moments are subjected to a continuity test to identify potential bad values.Confidence is estimated for each moment based on SNR, Gaussian fit of the spectral pointsused for the moments, the results of the continuity test, and proximity to contaminants.NIMA Tuning Case Study – January 7, 2003An example of tuning NIMA for a challenging site is given. The 915 MHz 3-beam profilerwith RASS is located in Dugway, Utah where the climate is very dry, resulting in windprofiler spectra that are characterized by very low SNR. RFI and occasional point targetsoften contaminate the spectra. Examples of typical spectra are shown in Figure 4.Figure 4. Examples of typical spectra from the Dugway profiler. Note the low signal to noise at mostrange gates and the RFI-like contamination symmetrically located at roughly ¾ the Nyquist velocity.The 30-minute consensus winds calculated from the POP moments using a constant windmodel are shown in Figure 5. Only at the low ranges are the resulting winds consistent andreasonable. The winds calculated from NIMA moments generated using the default NIMAconfiguration were also unsatisfactory. These included some large wind speeds that changeddirection by 180 degrees between consensus intervals indicating contamination by theapparent symmetric RFI signals at large Doppler velocities. The tuning effort thus focusedon detecting the atmospheric signal in the low SNR regions, identifying the weak RFI signals,and improving the preference for the atmospheric signal over the RFI signals.The Doppler peak detection was tuned to increase the reliance on the curvature fields as theseappeared to have higher skill than the some of the spectral intensity fields and the curvaturemembership maps were modified slightly as well. The overall threshold for Doppler peakswas lowered to allow the detection of the very weak signals.For RFI detection, the site-specific field was utilized to help detect the RFI signals thatappeared consistently in fixed locations. The RFI feature membership maps were modified toallow more tolerance in feature width, width variance, midpoint variance, and intensityvariance as the RFI signals were also contaminated with noise.The membership maps for atmospheric feature detection were also modified to account forthe contamination by noise. In particular, the feature SNR and intensity variance mapsrequired tuning. The overall threshold for categorizing a feature as atmospheric was loweredand both the Doppler peak score and feature SNR were de-emphasized while the overlap withRFI was given increased weight to help eliminate the RFI contamination.401
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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
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Fig. 1. Median (upper) winds and (l
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Fig.1. Lines of constant radial vel
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which have not yet been considered
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is calculated from the radiosonde t
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Figure 3: Time-altitude cross-secti
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Absorption of cosmic noise is cause
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Incoherent scatter spectracompared
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variations of spectral widths, refr
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Figure 1. Diurnal variation of Turb
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further experimental test of the ST
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waves can be observed more clearly
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winter and a minimum in summer near
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The main recently assumed mechanism
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Figure 2. Statistics of numbers of
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LIDAR OBSERVATIONS OF MIDDLE ATMOSP
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latitudinal dependence of the seaso
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APPLICATION OF THE DUAL-BEAMWIDTH M
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Figure 2: Mean zonal and meridional
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JLKLLK/ILIL6II/G/II/G/LEODFLK/LO/DD
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The monthly diurnal mean of horizon
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Session I.4: Meteorological Phenome
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Integration of the VHF wind profile
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Figure 1 : Map of the Lago Maggiore
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precipitating clouds, the cyclonic
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Eyewall(a)(b)(c)(d)Fig. 3: Radius-h
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as low as 0.55. The Piura 50-MHz ra
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place features in the profile with
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• Period 1 (June 1-10): SCCs exis
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Sumatera occurs by stratiform cloud
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very interesting to note the double
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20(a) Convective Region(b) Transiti
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Typhoon LekimaFig. 2 Typhoon Lekima
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Fig. 5 Passage of typhoon Hayan on
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the 50 cm 2 sensor head, enabling t
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22 June 2000 23:22:23 - 23:24:20 at
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the time-height section of a convec
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Thurai, M., T.Iguchi,T. Kozu, J.D.E
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There are two main mechanisms which
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Horel, J.D. and Cornejo-Garrido, A.
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estimating two independent and redu
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RASS THETA (K) RASS v-component (m/
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Surface winds usually range from 10
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weak (maximum of 5 m s -1 ) and the
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The vertical component from the VTB
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Figure 8 shows the profile of virtu
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2 3D ( , ) ( ) ( ) ˆ ( ) ˆp∆ xm
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presented in Praskovsky et al. (200
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In Fig. 2 a sketch of a mountain le
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In Fig. 8 the lamina is aligned on
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Figure 1: composite day (13 days) o
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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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Page 357 and 358: Session I.5: Operational Aspects an
Page 359 and 360: The profilers of WINDAS weredesigne
Page 361 and 362: NOAA, 1994 : Wind profiler assessme
Page 363 and 364: FIRST RESULTS OF THE BOUNDARY LAYER
Page 365 and 366: Figure 3. Pulse Design Diagram to s
Page 367 and 368: MOVEABLE UHF/S-BAND PROFILER/DISDRO
Page 369 and 370: one-minute Z values determined from
Page 371 and 372: TOWARD A MULTISENSOR GROUND BASED R
Page 373 and 374: 3. Cloud Evolution Case StudyOn the
Page 375 and 376: DEVELOPMENT OF A DIGITAL RECEIVER F
Page 377 and 378: Experiment 1 Experiment 2IPP 999Km
Page 379 and 380: ELECTRONIC DIGITAL BEAMFORMING IMPL
Page 381 and 382: The main element of the unit (figur
Page 383 and 384: .ON-LINE ADAPTIVE DC-GROUND-CLUTTER
Page 385 and 386: esulting in a widening of the bandw
Page 387 and 388: ON THE RADIATION EFFICIENCY OF COCO
Page 389 and 390: Table 2: Experiment #1 results, Tra
Page 391 and 392: A NEW NARROW BEAM MF RADAR AT 3 MHZ
Page 393 and 394: Off-zenith beams towards N, S, E, W
Page 395 and 396: 95ALWIN VHF radar: signal powerdB80
Page 397 and 398: ANTENNA BEAM VERIFICATION USING COS
Page 399 and 400: Figure 2: A 45 MHz reference sky te
Page 401 and 402: AN ATTEMPT TO CALIBRATE THE UHF STR
Page 403 and 404: is at 4.7 km, but in the first 4-ga
Page 405: QUALITY CONTROL FOR DOPPLER WIND PR
Page 409 and 410: SOUSY RADAR AT JICAMARCA: SYSTEM DE
Page 411 and 412: NEControl andcomputer roomCompCoute
Page 413 and 414: THE EQUATORIAL ATMOSPHERE RADAR:SYS
Page 415 and 416: Table 1: Specifications of the EAR
Page 417 and 418: VHF ATMOSPHERIC AND METEOR RADAR IN
Page 419 and 420: ased upon a geotechnical engineerin
Page 421 and 422: VORTICAL MOTIONS OBSERVED WITH THE
Page 423 and 424: interpolation from the original gri
Page 425 and 426: A NEW MINIRADAR TO INVESTIGATE URBA
Page 427 and 428: e eliminated to analyze correctly t
Page 429 and 430: Session PWG 1: System Calibrations
Page 431 and 432: Session PWG 2: Data Analysis, Valid
Page 433 and 434: • the time series vectors x(k) of
Page 435 and 436: Fig. 4: reflectivity of the hydrome
Page 437 and 438: Session PWG 3: Accuracies and Requi
Page 439 and 440: Session PWG 4: International Collab
Page 441 and 442: Session II.E: NOVEL PERSPECTIVES AN
Page 443 and 444: 2 Proposed AlgorithmReceived signal
Page 445 and 446: N#4E-1-16E1A1#1#2A-1-1C1#3C-1-19Fig
Page 447 and 448: of conventional DCMP, with which th
Page 449 and 450: applying the directional constraint
Page 451 and 452: while for a beam of finite width, t
Page 453 and 454: In order to make the process more q
Page 455 and 456: 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
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Hysell, David L.EAS/Cornell Univers
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Silva, Robert R.ATRADAustraliarsilv
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AAdachi, A. .......................
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TTabary, P. .......................
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