November 15, 2012

"Monster waves" in the North Sea

On average, two ships have been lost each week worldwide in recent years because of bad weather. In many cases they probably fell victim to "monster waves." These are individual waves of extraordinary height or with an abnormal shape that so far cannot be adequately counteracted by ship construction. The existence of monster waves was long doubted. But the latest remote sensing data and continuous monitoring at offshore platforms has revealed many cases of such extreme events on the open sea. Research at the DLR Earth Observation Center (EOC) is helping to elucidate this phenomenon.

EOC researchers could show that in the North Sea, wave groups of abnormal height are associated with atmospheric effects. Systems of wind gusts extending 30 km and more can generate discrete groups of very high, long waves. To do this, the gusts have to move across the North Sea about as fast as the long ocean waves. In this way the wind continuously supplies the waves with energy and allows them to grow. These gusts are associated with characteristic cloud formations.

While cloud formations can be measured by optical satellite sensors, surface winds are ascertained with microwaves (Synthetic Aperture Radar, SAR). The methodology developed at EOC makes use of the roughness of the ocean surface to derive wind speed. Over areas with storms during which extremely high individual waves occur, satellite images in the thermal infrared and visible spectral range reveal noteworthy, ring-shaped, cloud formations 30 to 90 kilometers in size. These “open cells” arise as cold air flows from the north over the relatively warm North Sea. SAR measurements confirm that the open cells cause a local increase in wind velocity, with the strongest increase occurring at the leading edge. The scientists compared the data from two radar satellites collected at an interval of 30 minutes and in this way were able to show the continuous movement of the entire gust system and estimate its velocity. Based on satellite data they could demonstrate that the mesoscale gusts spread out as an organized system approximately at the velocity of the long ocean waves. Since these wind gusts are, however, not depicted in the wind fields of atmospheric forecast models, current wave models cannot predict the monster waves that arise in this manner. Early warning was not possible until now.

The EOC research team is thus investigating how warning of such extreme waves can be given. It simulated Storm Britta of November 2006 on a computer. At that time extreme waves had damaged the 18 meter high deck of the FiNO-1 research platform. For the simulation in a numeric spectral wave model the wind fields from a conventional atmospheric model were modified according to the measurements deduced from the SAR data by superimposing the gusts into coarse input wind field. The simulations showed that a single “open cell” caused on average a local increase in wave height of about three meters. But a cluster of cells led to a local increase up to six meters. In the simulation extreme waves were formed most commonly of a wave length of 400 meters, in groups, and only in a narrow strip about two-and-a-half kilometers wide. Locally, such as on a platform, they can only be seen as the cell passes by within a short time window of about 10 to 20 minutes. The results of the simulation precisely matched the observations made during Storm Britta.

Thanks to these research results, early warning systems can be developed in the future to warn of monster waves and thereby help to prevent ship accidents and damage to platforms or offshore wind energy converters.

More detailed information on this subject can be found in "Storm Observations by Remote Sensing and Influence of Gustiness on Ocean Waves and on Generation of Rogue Waves" by A. Pleskachevsky, S. Lehner and W. Rosenthal (see link at right), as well as in "Synergetic Use of Radar and Optical Satellite Images to Support Severe Storm Prediction for Offshore Wind Farming" by S. Brusch, S. Lehner and J. Schulz-Stellenfleth.

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