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d%r( x ) ⎡ rC( x , ) ⎤ 4 ⎡ r rc ( x ) c ( x ) ⎤ rexp 2 c ( x )[ ]2 2 2 22∆mk=− ∂ ∆mkτ ∂ τ =2∆mk−1∆mk−0∆⎣⎦mkτ = 0⎣⎦22 2( πγ ) ( )4 4 δ 2 2 α 4 4 πγ 2 2 α2 2r r r= d ( ∆ x ) + 256 ∆x t u D exp −4∆x Dmk mk mk mkd% r( x ) ⎡ rC ( x , ) ⎤ r r4 c ( x ) d ( x )(29)222auto a, k=−⎢∂auto a, kτ ∂ τ =auto a, k=auto a,k⎣⎥⎦τ= 0where d , d , d , and 0 1 2dautoare given by Eqs. (8), (9), (11), and (12).COMPARISON OF THE TECHNIQUESA good agreement between STARS and CF-based SA techniques FCA and HAD inmeasuring the mean horizontal winds U , V , and intensity of the vertical turbulentvelocity2w(28)was found for the NCAR Multiple Antenna pro<strong>file</strong>r and the Middle and UpperAtmosphere radar, respectively (Praskovsky et al., 2003c, d, e). The agreement seems to beexpected because STARS is related to the CF-based techniques; see the previous section.However, the relations between the SF and CF do not indicate the equivalence betweenSTARS and HAD (or any other) CF-based technique. Below we show that the CF and SFbasedSA techniques are conceptually different in spite of being formally related to eachother for a particular case of the second order functions.CF can be applied only to the globally statistically stationary random processes. Realphysical processes are almost never globally stationary while practically any process can besafely considered as being the locally statistically stationary; e.g., Tatarskii (1971), andMonin and Yaglom (1975). The basic STARS Assumption 1S about a local stationarity ismuch less restrictive than the basic HAD Assumption 1H about a global stationarity. Anotherimportant feature of SF is the presence of a small parameter τ → 0 . The small parameteralways significantly simplifies a physical task by both leading to the asymptotically exactsolutions, and requiring a smaller number of less restrictive assumptions; e.g., Migdal (1977).Indeed, the STARS Assumptions 2S and 3S for estimating the mean horizontal winds are lessrestrictive than the HAD Assumptions 2H - 4H. Furthermore, STARS requires only twoadditional Assumptions 4S and 5S for deriving operational equations for turbulence2 2 2characteristics w , u , v , and uv while HAD requires four much restrictive2additional Assumptions 5H - 8H for estimating the only turbulence characteristic w .CF characterizes fluctuations of a random process at all scales but mainly at the large onesof the order of the process's integral time scale T cor. Fluctuations at large scales are heavilyaffected by external conditions, and the functional form of CF can never be universal; e.g.,Townsend (1956, secs. 1.8, 1.9). In particular, the Gaussian functions (15) and (16) in theHAD technique are merely good approximations near the peak values of the auto and crossCF; in practice the rigorous validity of Eqs. (15) and (16) over a wide range of τ would bemore an exception than a rule. SF characterizes fluctuations at small scales τ
Only the second order SF are considered in this paper. As shown in PPa, SF of anyorder p ≥ 2 can be derived for a pair of received signals and applied to practicalmeasurements while CF at only p = 2 are used in SA techniques. It is important thatequations for SF at p > 2, for example those for estimating the higher-order turbulencecharacteristicsw3 ,u3 ,v3 ,w4,u4,4v , and so on, can be derived using thesame Assumptions 1S - 5S as at p = 2 (PPa). Therefore, SF is a more powerful theoreticaltool than CF which has been well recognized in the turbulence research; e.g., Tatarskii(1971), and Monin and Yaglom (1975).However, the major difference between CF and SF-based SA techniques is not in theabove theoretical details but rather in the physical concept beneath the techniques. The crossr rCF (14) describes the similarity between signals from two receivers Ex (ak ,+∆ xmk, t+τ ) andrE( xak,, t)at all temporal separations −∞< τ
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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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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
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
Page 457 and 458: Enhanced resolution applyingpulse s
Page 459 and 460: Beckmann, Spizichino, 1964Fig. 8 Po
Page 461 and 462: Fig. 11 Plots of temporal variation
Page 463 and 464: Fig. 14 Distributions of phase cent
Page 465 and 466: Hocking, W.K., Radar studies of sma
Page 467 and 468: THE STRUCTURE FUNCTION-BASED APPROA
Page 469 and 470: { Ui( t), Vi( t), Wi( t)} = { Ui ,
Page 471: 161). Assumption 2H: the instantane
Page 475 and 476: fluctuations umk( t ) along the bas
Page 477 and 478: VHF PARASITIC RADAR INTERFEROMETRYF
Page 479 and 480: • All the costs of transmitter pr
Page 481 and 482: Figure 2: Example of range-azimuth
Page 483 and 484: Target Altitude, km1009080706050403
Page 485 and 486: ReferencesGriffiths, H. D., A. J. G
Page 487 and 488: 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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