Sensitivity of HF radar-derived surface current self-organizing maps to various processing procedures and mesoscale wind forcing

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• 作者：Ivica Vilibić ; Hrvoje Kalinić ; Hrvoje Mihanović ; Simone Cosoli…
• 关键词：Self ; organizing maps ; Ocean surface currents ; Mesoscale meteorological models ; Adriatic Sea
• 刊名：Computational Geosciences
• 出版年：2016
• 出版时间：February 2016
• 年：2016
• 卷：20
• 期：1
• 页码：115-131
• 全文大小：4,249 KB
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• 作者单位：Ivica Vilibić (1)
  Hrvoje Kalinić (1)
  Hrvoje Mihanović (1)
  Simone Cosoli (2) (3)
  Martina Tudor (4)
  Nedjeljka žagar (5)
  Blaž Jesenko (5)
  
  1. Institute of Oceanography and Fisheries, Šetalište I. Meštrovića 63, 21000, Split, Croatia
  2. Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, Borgo Grotta Gigante 42/c, 34010, Sgonico, Trieste, Italy
  3. School of Civil, Environmental and Mining Engineering, University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia
  4. Meteorological and Hydrological Service, Grič 3, 10000, Zagreb, Croatia
  5. Faculty of Mathematics and Physics, University of Ljubljana, Jadranska 19, 1000, Ljubljana, Slovenia
  
• 刊物类别：Mathematics and Statistics
• 刊物主题：Mathematics
  Mathematical Modeling and IndustrialMathematics
  Geotechnical Engineering
  Hydrogeology
  Soil Science and Conservation
  
• 出版者：Springer Netherlands
• ISSN：1573-1499

文摘

We performed a number of sensitivity experiments by applying a mapping technique, self-organizing maps (SOM) method, to the surface current data measured by high-frequency (HF) radars in the northern Adriatic and surface winds modelled by two state-of-the-art mesoscale meteorological models, the Aladin (Aire Limitée Adaptation Dynamique Développement InterNational) and the Weather and Research Forecasting models. Surface current data used for the SOM training were collected during a period in which radar coverage was the highest: between February and November 2008. Different pre-processing techniques, such as removal of tides and low-pass filtering, were applied to the data in order to test the sensitivity of characteristic patterns and the connectivity between different SOM solutions. Topographic error did not exceed 15 %, indicating the applicability of the SOM method to the data. The largest difference has been obtained when comparing SOM patterns originating from unprocessed and low-pass filtered data. Introduction of modelled winds in joint SOM analyses stabilized the solutions, while sensitivity to wind forcing coming from the two different meteorological models was found to be small. Such a low sensitivity is considered to be favourable for creation of an operational ocean forecasting system based on neural networks, HF radar measurements and numerical weather prediction mesoscale models.