GUIDE WAVE ANALYSIS AND FORECASTING - WMO

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98 Range in km 67.5 60.0 52.5 45.0 37.5 30.0 22.5 15.0 Ground-wave radars use vertically polarized radio waves in the HF band and must be located on a sea coast, island, platform or ship. Coverage of 0–200 km in range is achievable. The potential for continuous seastate monitoring is shown in Figure 8.8. Recent work indicates that two stations some distance apart can triangulate on particular sea areas and can yield maps of directional spectra with a one-hour update. Sky-wave radars are large installations, but can be located well back from the sea coast as they employ radio waves travelling by way of the ionosphere. Coverage extends from 900 to 3 000 km. Surface wind direction measurement is readily achieved, but ionospheric variability limits wave-height measurement (Barrick and Gower, 1986). 8.5.8 Comparison of remote-sensing methods Platform-based microwave sensors fulfil a useful role for point measurement in environments where buoys are a hazard. HF ground-wave radars promise to provide maps of spatial-temporal wave spectra (if necessary, at hourly intervals), up to 200 km from the coast. Sky-wave radars extend coverage to oceanic areas, particularly for tracking fronts and hurricanes, but suffer ionospheric limitations (Georges and Harlan, 1994). Satellite altimeters, scatterometers and radiometers provide worldwide coverage of wave height and surface wind for modest telemetry and processing overheads. Data close to coastlines can be suspect, either due to land in the sensor footprint or to a delay in the sensor switching from land to ocean mode as the satellite ground track moves from land to sea. Spatial and temporal coverage of the Earth is constrained by the satellite orbit. The satellite usually has an exact repeat cycle of between three and 35 days. The spacing between tracks is inversely proportional to the repeat cycle — from about 900 km (three-day cycle) to 80 km (35-day cycle) at the Equator. Satellite data are therefore particularly suitable for long-term wave climate studies, but they can also be incorporated, with other observations, into numerical forecast models or used for validating hindcast data. Satellite synthetic aperture radars require expensive real-time telemetry and off-line processing. Difficulty is GUIDE TO WAVE ANALYSIS AND FORECASTING December 8 9 10 experienced in imaging waves travelling parallel to the satellite track and waves travelling in any direction if the wavelength is less than about 100 m. But research indicates that SAR data can be used with wave models to give improved estimates of directional wave spectra. 8.6 Wave data in numerical models Wave models are being increasingly used, not only for predicting wave conditions a few hours or days ahead, but also for deriving wave climate statistics (see Section 9.6.2 et seq.). Wave data are needed to validate the models, and they have recently (since 1992) also been used in model initializations. The assimilation of wave data into a model, reinitializing the model at each time step, can improve its performance, and considerable activity is under way to develop techniques for doing this. Satellite data, with their global coverage, are especially useful. Table 8.1 lists countries at present carrying out research into the assimilation of satellite data into wave models, and indicates those which are using the data in their operational wave models. Data from the satellite altimeter are most readily and widely available, but the only wave parameter it measures is significant wave height. How best to incorporate this one value into a model’s directional wave spectrum has been addressed in several studies and workable solutions found (see, for example, Thomas, 1988). 8.7 Analysis of wave records Figure 8.8 — Time history of significant wave height vs range, as measured by HF groundwave radar (after Wyatt et al., 1985) Nowadays, most wave data are collected digitally for subsequent computer analysis. Data are commonly either transmitted from the measurement site by radio link or by satellite (e.g. via ARGOS), or recorded locally (e.g. on board a buoy). A number of systems are available for real-time presentation of data in the form of time series plots or statistical presentations. In addition to providing information suitable for operations, such systems also give an immediate indication of the correct functioning of the system. Traditionally, however, analysis was carried out by a manual technique based on analogue chart records (see also Section 1.3).
8.7.1 Digital analysis of wave records Wave measurements are analysed over, typically, a 20- to 35-minute record with values of wave elevation sampled every 0.5–2 seconds. Measurements are then taken either continuously (for operational monitoring) or threehourly for long-term data collection, although continuous measurements are becoming more standard. A preferred oil-industry standard for the measurement and analysis of wave data has been given by Tucker (1993). The most commonly used wave analysis nowadays estimates the (directional) wave spectra (Section 1.3.7) using Fast Fourier Transform techniques and hence computes a standard set of wave parameters (e.g. H m0, T m02). In the case of directional wave measurements, two additional parameters are commonly analysed and stored for future use. These are the mean wave direction, θ 1, the directional spread, σ, at each frequency of the wave WAVE DATA: OBSERVED, MEASURED AND HINDCAST 99 TABLE 8.1 On-going projects on the assimilation of remotely sensed data in ocean wave models (R = Research project; O = Operational project (with starting date in brackets). Collated from responses to a WMO survey of Member states) Members/ Project status Data Data origin Investigators organizations Australia R SAR ERS-1 I. Jones O Altimeter G. Warren R Scatterometer R. Seaman R/O HF sky-wave radar Jindalee T. Keenan Canada R/O (1994) SAR (wave mode) Radarsat L. Wilson ERS-1/ERS-2 M. L. Khandekar R. Lalbeharry ECMWF R/O (1993) SAR ERS-1 (Fast delivery products) A. Guillaume Altimeter France R Altimeter ERS-1 J. M. Lefèvre Topex-Poseidon Germany R SAR GEOSAT S. Hasselmann Altimeter ERS-1 Netherlands R/O (1992) Altimeter ERS-1 G. Burgers V. Makin Japan R SAR GEOSAT H. Kawamura Scatterometer ERS-1 Altimeter Topex-Poseidon Microwave-radiometer New Zealand R Scatterometer GEOSAT A. Laing Altimeter ERS-1 Norway R Altimeter ERS-1 M. Reistad O SAR United Kingdom R/O (1992) Altimeter ERS-1 (Fast delivery products) S. Foreman USA R/O (1993) SAR ERS-1 D. Esteva Scatterometer W. Gemmill Altimeter spectrum (see, for example, Ewing, 1986) and associated directional wave parameters such as the wave direction at the spectral peak period. Full directional wave analysis in real time is also commonly available from commercial wave measuring systems. 8.7.2 Manual analysis of chart records A rapid analysis of a 10-minute chart record, similar to that illustrated in Figure 8.1 (or Figure 1.14), can be made in the following widely-used manner. This was originally presented by Tucker in 1961, and is more widely available in Draper (1963) and interpreted by Draper (1966) for practical application. Measure the height of the highest crest above the mean (undisturbed) water level, label this A. Measure the height of the second highest crest, B. Similarly, measure the depths of the lowest, C, and second lowest, D, troughs: A + C = H1 B + D = H2.
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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
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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 and 106: 80°N 60°N 40°N 20°N 0° -20°S
Page 107: a combination of sea-surface temper
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.
Page 157 and 158: 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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GUIDE WAVE ANALYSIS AND FORECASTING - WMO

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