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Kauai, HIProjectAt-sea demonstration testing of the Lockheed-Martin Tactical Environmental Processor (TEP) was conducted during December 1999 immediately west of Kauai, HI. TEP extracts detailed meteorological data from U.S. Navy phased array surveillance radars. During this experiment, the prevailing wind at Kauai was from the east-northeast and the destroyer USS O’Kane was operating its radar on the leeward side of the island. Substantial azimuthal variability was observed in the radar sea clutter returns, which we find to be consistent with the presence of an island wake. Sea clutter returns can be a serious problem for surveillance radars because return signals from low-flying targets may be masked and go undetected. The evaporation duct often enhances sea clutter returns and may yield signal levels at ranges well beyond the horizon (Paulus, 1990). Rogers et al. 2001 demonstrate that it is possible, by inversion techniques, to infer refractivity structure (e.g., EDH) based upon radar measured clutter return power. Here we examine the dynamics creating the Kauai wake and the impact of the wake upon the refractivity field, particularly the EDH distribution. High-resolution mesoscale real data forecasts are conducted that encompass the time period (3 December 1999) of the TEP demonstration experiment. The Navy’s Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) is used in this study (Hodur 1997).
ResultsFigure 1 shows a parcel trajectory and the low-level wind speed as the flow is deflected around the island of Kauai in a preliminary idealized simulation. A real data forecast valid 6 UTC 3 Dec 1999 reveals a substantial wake evident in the EDH field (Fig. 2). The wake extends in a continuous manner downwind of the island for a distance of ~150 km and then becomesa broken field having multiple local maxima that are associated with eddies that have shed from the island and regions of convection. As a consequence, the EDH field contains much more inhomogeneity in the lee of the island, beyond just that across the wake itself, than is found upwind of the island. Although we are unable to verify this aspect of the forecast with the data available on this day, we are able to make model comparisons with the radar clutter data gathered aboard the USS O’Kane. 1. The Georgia Institute of Technology (GIT) sea clutter model is used to compute the normalized radar cross section, s0, as a function of radar wavelength (l), y, q, V, and average wave height, hav. Figure 3a shows the observed clutter map taken aboard the USS O’Kane, while Fig. 3b displays the modeled clutter map. (The observed clutter map shows the islands of Kauai and Niihau, while the modeled map does not.) By design, the modeled azimuthally averaged clutter power at 10 km agrees with the observed average at this range; however, otherwise the computed azimuthal and range dependence is freely determined by the following linkage of models: COAMPS forecast fields --> similarity theory computed EDH --> EM propagation model --> Clutter model. The red lines represent the maximum range of clutter power (in 100 sectors) taken from the observations and placed on Fig. 3b for comparison with the modeled clutter power ranges. Qualitatively, the modeled map displays many of the features of the observed clutter map. They both have clutter power extending further out in range in the northerly and southerly directions from the center (i.e., from the radar). This coincides with the higher wind speed and larger EDH’s in those directions. Looking toward the island of Kauai (900 radial), and the island of Niihau (250-2600 radials), the clutter falls off much more rapidly; this is indicative of lower EDH’s and speeds within the island wake. The island of Niihau, however, does appear to perturb the clutter field more than is represented by the modeled clutter map. The RMS difference between the model predicted and the observed clutter is ~1.5 dB. ReferencesSee the publication by Burk et al. (2003) for the details of this study and for the citations listed above. |
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Figure 1. Idealized simulation showing a sinuous pattern in10-m wind speed and wind arrows in the wake of the island of Kauai, HI. The purple trajectory along the south side of the island indicates the abrupt displacement of parcels due to the mountain wake dynamics.

Figure 2. Evaporation duct height (m) from a real data assimilation forecast for 6 UTC 3 Dec 1999.


several EM propagation codes.
Last Modified: Monday, 27-Mar-2006 14:25:00 PST