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Integrating Local Ocean Weather Knowledge for Model Validation by Matthias Mueller

Explore the integration of local ocean weather knowledge in validating FjordOs models. Learn about generating reliable data, comparison with numerical models, and the impact on shipping. Discover the process, results, and reflections to enhance validation quality.

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Integrating Local Ocean Weather Knowledge for Model Validation by Matthias Mueller

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  1. Local oceanweather knowledge Extraction and application for validation Matthias Mueller, HBV

  2. Outline • Motivation • WorkingProcess • NumericalModel • Interview Guide • Local Knowledge • Results • Reflection • Outlook Matthias Mueller, HBV

  3. Motivation (I) • Include local knowledge in thevalidation of FjordOsmodels • To whatextent do theoceanweatherconditions from theexistingmodelcomplywiththeexperience from local people? • How to generate reliable data and valid conclusionsthatcan support theresults from the computer model? • How to compareexperience from local peoplewithresults from numericalmodels? Matthias Mueller, HBV

  4. Motivation (II) • Quality of knowledge • Methodologicalapproach as pioneerwork • Practice-relatedresearch and findings • Effectson shipping Matthias Mueller, HBV

  5. Area of Interest 20 km Matthias Mueller, HBV 20 km

  6. WorkingProcess • Validation • Analysis • Interview Guide • Verification • Extraction & Selection • Acquisition of local knowledge Matthias Mueller, HBV

  7. ROMS75 Model Matthias Mueller, HBV

  8. Interview Guide Matthias Mueller, HBV

  9. Local Knowledge: Participants 1) Based on field notes instead of audio recording. 2) Short in time due to on-board duties. 3) Field trip to Revlingen and Mossesundet. 4) With the opportunity to observe some of the described phenomena. Matthias Mueller, HBV

  10. Local Knowledge: Phenomena (I) NB: Size and direction of arrows is indicativeonly! Matthias Mueller, HBV

  11. Local Knowledge: Phenomena (II) P8 NB: Size and direction of arrows is indicativeonly! P11 P6 Matthias Mueller, HBV

  12. Secondary Sources • Verification of selectedphenomenabeforemodelvalidation Matthias Mueller, HBV

  13. Results • Validation during high, outgoing, low, and incoming tide • Unexpectedissues: Revlingen &Vansjø Matthias Mueller, HBV

  14. Reflection • Identifynew areas of interest • Indicatethecapacity • Methodologicaltriangulation for validationquality Matthias Mueller, HBV

  15. Outlook • Available local knowledge • Validation withextractedphenomena • Extraction of furtherphenomena • Additional local knowledge • Sample size • Dynamicprocess Matthias Mueller, HBV

  16. Thankyou. Matthias Mueller, HBV

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