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Global Ocean Physics Reanalysis | Data Processing for MLD Analysis in Python

Rp 200.000,00

  • USD: 12,51$

Global Ocean Physics Reanalysis | Data Processing for MLD Analysis in Python teaches oceanographers and data enthusiasts to analyze Mixed Layer Depth (MLD) using Python and reanalysis data from Copernicus Marine Service. Participants will learn to access, preprocess, and visualize ocean physics reanalysis data, calculate MLD using temperature and density thresholds, and explore spatiotemporal trends. Through hands-on exercises, learners will develop skills to process ocean data confidently for research or practical use. Perfect for students, researchers, and professionals in oceanography and climate science.

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This course is designed to equip oceanographers and data enthusiasts with the skills to analyze Mixed Layer Depth (MLD) using Python and reanalysis data from the Copernicus Marine Service.

Learning Objectives
Upon completion of this course, participants will be able to:

  1. Access and retrieve reanalysis data from Copernicus Marine Service.
  2. Preprocess ocean physics data for MLD analysis.
  3. Apply temperature and density threshold methods to calculate MLD.
  4. Visualize spatiotemporal trends in MLD using Python.
  5. Develop confidence in processing and analyzing oceanographic datasets.

Target Audience
This course is perfect for:

  • Researchers aiming to integrate MLD analysis into their projects.
  • Students seeking practical experience with oceanographic data.
  • Professionals in oceanography, climate science, and related fields.

Key Topics Covered

  • Introduction to ocean reanalysis data and the Copernicus Marine Service.
  • Fundamentals of Mixed Layer Depth: definitions, importance, and methods of calculation.
  • Data preprocessing
  • Hands-on Python exercises for MLD calculation and visualization.
  • Exploring and interpreting spatiotemporal patterns in ocean stratification.

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