GUIDE WAVE ANALYSIS AND FORECASTING - WMO

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96 the SAR image. Our problem is to go the other way: to derive the directional wave spectrum given the SAR image. Research has shown that if a global wave model is run to provide an initial estimate of the wave spectrum, then the difference between the observed SAR spectrum and that estimated from the model spectrum can be used to correct the model spectrum and hence to improve the wave model output (Hasselmann et al., 1991). A practical problem with SAR, which tends to inhibit its use, is the vast quantity of data it produces (108 bits per second) and the consequent cost of processing and acquiring the data. Moreover, these data cannot be stored on board the satellite, so SAR data can only be obtained when the satellite is in sight of a ground receiving station. An exception to this is the ERS-1 which obtains a small SAR image, with a footprint of 5 x 5 km, every 200 km. These “wave vignettes” can be stored on board and transmitted later to ground. 8.5.6 Microwave radiometry As well as reflecting incident radio waves, the sea radiates thermal radio noise as a function of its temperature and emissivity; this radiation can be detected by a microwave radiometer (analogous to an astronomer’s radio telescope). The emissivity varies with surface roughness, amount of foam and, to a small extent, with salinity. Thus the signal received at the antenna is mainly GUIDE TO WAVE ANALYSIS AND FORECASTING Secondary component Ocean wavelength (metres) Figure 8.6(a) (left) — SEASAT SAR image of the wave field between the Islands of Foula and Shetland (ESA photograph, processed at the Royal Aircraft Establishment, United Kingdom) Figure 8.6(b) (below) — Examples of directional wave-energy spectrum derived by digital processing of SEASAT synthetic aperture radar data. The five levels of greyness indicate spectral amplitude, while the distance from the centre represents wavenumber (2π/λ). The circles are identified in wavelength. A 200 m swell system is shown coming from ESE and broader spread 100 m waves coming from ENE. The analysis has an 180° ambiguity (after Beale, 1981) Spacecraft velocity vector Primary component Image energy density (linear scale)
a combination of sea-surface temperature and wind effects, modified by atmospheric absorption and emission due to water vapour and cloud liquid water. Since the sensitivity to each of these parameters is frequency dependent, a multichannel radiometer can be used to separate them. The sea-surface temperature data complement infra-red values in that they can be obtained through cloud, though with less accuracy and poorer spatial resolution. Wind speed can be derived over a broader swath WAVE DATA: OBSERVED, MEASURED AND HINDCAST 97 Figure 8.7 — ERS-1 SAR sub-scene acquired on 17 January 1993 by the ESA station in Fucino, Italy. The image shows the entrance to the Ria de Betanzos (Bay of La Coruña), north-western Spain. The image represents an area of 12.8 x 12.8 km. An east-southeast swell (i.e. travelling from west-northwest) enters the bay and the waves are diffracted as they travel through the narrower opening of the bay. However, waves do not enter the very narrow northern Ria de El Ferrol. The inner part remains wind and wave sheltered and therefore dark. As the waves get closer to the shore their length becomes shorter, as can be observed near the coast to the north. The long linear feature through the middle of the image is probably linked to a strong current shear, not usually visible in such a sea state (image copyright: ESA; J. Lichtenegger, ERS Utilisation Section, ESA/ESRIN, Frascati) than from the present satellite scatterometer, but no estimate of wind direction is obtained. 8.5.7 Ground-wave and sky-wave HF radar HF radar (employing the high frequency band, 3–30 MHz, wavelength 100–10 m), is of value because it is capable of measuring wave parameters from a ground station to ranges far beyond the horizon, utilizing the Doppler spectrum of the sea echo (E. D. R. Shearman 1983, Barrick and Gower 1986, Wyatt and Holden, 1994).
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WORLD METEOROLOGICAL ORGANIZATION G
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© 1998, World Meteorological Organ
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IV Chapter 7 - WAVES IN SHALLOW WAT
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ACKNOWLEDGEMENTS The revision of th
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VIII has been included particularly
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X considerable attention. Annex III
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2 η Crest Zero level a H = 2a a Tr
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4 Figure 1.5 — Paths of the water
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6 When waves propagate into shallow
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8 1.3.2 Wave groups and group veloc
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10 wavelengths in a given sea state
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12 for instance, a frequency of 0.1
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14 in which E(f) is the variance de
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16 2.1.1 Wind and pressure analyses
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18 GUIDE TO WAVE ANALYSIS AND FOREC
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20 Figure 2.2(a) (right) — Usual
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22 As a quick approximation of ocea
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24 GUIDE TO WAVE ANALYSIS AND FOREC
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26 Gr G Gr ∇p C Cnf ∇p C Cnf
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28 POINT C — The effect of warm a
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30 a general sense, and can be appl
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32 Free atmosphere Ekman layer Cons
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3.1 Introduction This chapter gives
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ange of directions. Also, waves at
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small enough that swell can survive
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Figure 3.7 — Structure of spectra
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4.1 Introduction CHAPTER 4 WAVE FOR
Page 55 and 56: necessary to forecast waves for a p
Page 57 and 58: TABLE 4.4 Additional wave informati
Page 59 and 60: TABLE 4.6 Ranges of swell periods a
Page 61 and 62: this situation, the angular spreadi
Page 63 and 64: the energy flux is c gH 2 . This is
Page 65 and 66: α0, degrees Solution: 80° 70° 60
Page 67 and 68: 5.1 Introduction National Meteorolo
Page 69 and 70: only once, since it is usual to sto
Page 71 and 72: Frequency 0.050 0.067 0.083 0.100 0
Page 73 and 74: The models may differ in several re
Page 75 and 76: The CH class may include many semi-
Page 77 and 78: 6.1 Introductory remarks Since the
Page 79 and 80: in some applications, the zero up/d
Page 81 and 82: OPERATIONAL WAVE MODELS 71 Figure 6
Page 83 and 84: give large differences in the compa
Page 85 and 86: Wind (m/s) Waves (m) Buoy/GSOWM Wav
Page 87 and 88: TABLE 6.2 Numerical wave models ope
Page 89 and 90: TABLE 6.2 (cont.) Country Name of m
Page 91 and 92: 7.1 Introduction The evolution of w
Page 93 and 94: water boundary into shallow water.
Page 95 and 96: eflected waves, although the latter
Page 97 and 98: Energy (cm 2 /Hz) Energy (cm 2 /Hz)
Page 99 and 100: 8.1 Introduction Wave data are ofte
Page 101 and 102: matter and timing the intervals bet
Page 103 and 104: a Directional Waverider (Barstow et
Page 105: 80°N 60°N 40°N 20°N 0° -20°S
Page 109 and 110: 8.7.1 Digital analysis of wave reco
Page 111 and 112: 9.1 Introduction Chapter 8 describe
Page 113 and 114: Presentation of data and wave clima
Page 115 and 116: the monsoon season of June to Septe
Page 117 and 118: Probability of non-exceedance case
Page 119 and 120: individual wave height derived usin
Page 121 and 122: emote, data-sparse areas. However,
Page 123 and 124: TABLE 9.2 (cont.) Country Source of
Page 125 and 126: For a storm hindcast, select the mo
Page 127 and 128: TABLE 9.3 (cont.) Country Model use
Page 129 and 130: ANNEX I ABBREVIATIONS AND KEY TO SY
Page 131 and 132: Abbreviation/ Definition Symbol MOS
Page 133 and 134: CODE FORM: D . . . . D or IIiii* SE
Page 135 and 136: sensors, spectral peak wave period
Page 137 and 138: cs1cs1 The ratio of the spectral de
Page 139 and 140: M jM j n mn m n smn sm n bn bn b P
Page 141 and 142: 1744 Im Indicator for method of cal
Page 143 and 144: The following distributions are bri
Page 145 and 146: 4. Weibull distribution Probability
Page 147 and 148: 8. Fisher-Tippett Type I (FT-I) (or
Page 149 and 150: ANNEX IV THE PNJ (PIERSON-NEUMANN-J
Page 151 and 152: ANNEX IV 141 Duration graph. Distor
Page 153 and 154: REFERENCES Abbott, M. B., H. H. Pet
Page 155 and 156: REFERENCES 145 Carter, D. J. T., P.
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REFERENCES 147 Gumbel, E. J., 1958:
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REFERENCES 149 Maat, N., C. Kraan a
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Slutz, R. J., S. J. Lubker, J. D. H
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SELECTED BIBLIOGRAPHY CERC, 1984: C
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156 Energy . . . . . . . . . . . .
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158 steepness . . . . . . . . . . .
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