Wavy

Welcome to wavy!

Introduction

wavy is an open source package (under development) with the aim of easing the task of wave model validation. The user can either choose in-situ observation files or remote sensing files to extract time-series and/or collocate with wave model output.

Note

This project is under active development. I try to keep the documentation pristine. Please do not hesitate to contact me if you experience troubles, have questions, or would like to contribute.

Contents

• Installing
• Tutorials
  • Setting up a project and wavy config files
  • Use satellite data
  • Use multiple satellite missions
  • Define regions of interest
  • Apply filters
  • Read model data
  • Read in-situ observations (.d22, netcdf/thredds, FROST API)
    • read .d22 files
    • make a FROST call
    • read .nc-files
  • Use multiple insitu-sources
  • Follow storm track
  • Consolidate multiple retrievals
  • Collocating model output and observations
    • Collocation of satellite and wave model
    • Collocation of in-situ data and wave model
    • Dump collocation ts to a file for later use
  • Validate the collocated time series
  • Validation metrics
  • Gridded satellite observations and statistics
    • Gridding of satellite observations
    • Gridding of collocated data
  • Quick look examples with wavyQuick
• Vietnam Validation Workshop 2021
  • 1. wavy config files
  • 2. download L3 satellite altimetry data
  • 3. download L2P and L3 CCI multi-mission satellite altimetry data
  • 4. read satellite data
    • L3 data from cmems
  • 5. access/read model data
  • 6. collocating model and observations
    • Collocation of satellite and wave model
  • 7. dump collocation ts to a netcdf file
  • 8. validate the collocated time series
  • 9. quick look examples
  • 10. Vietnam examples
    • Add model
    • Download satellite data
    • Usage in python
    • wavyQuick use for vietnam model
• Vietnam Validation Workshop 2022
  • 1. Collocating satellite tracks with ship route
  • 2. Collocating model output with ship route
  • 3. Comparing model, satellite and observations from the ship
• Vietnam Validation Workshop 2022 #2
  • 1. wavy config files
  • 2. Download L3 satellite altimetry data
  • 3. Read satellite data
    • Exercise:
  • 4. access/read model data
  • 5. Collocating model and observations
    • Collocation of satellite and wave model
  • 6. Validate the collocated time series
• One Ocean Expedition
  • 1. Collocating satellite tracks with drifter
  • 2. Collocating model output with drifter
• Gallery
• API Reference
  • wavy
    • Submodules

Credits

• Bohlinger, P., Breivik, Ø., Economou, T., Müller, M.: A novel approach to computing super observations for probabilistic wave model validation, Ocean Modelling, 139, https://doi.org/10.1016/j.ocemod.2019.101404, 2019.

Studies that used wavy

• Rabault, J., and Coauthors, 2022: Openmetbuoy-v2021: An easy-to-build, affordable, customizable, open-source instrument for oceanographic measurements of drift and waves in sea ice and the open ocean. Geosciences, 12 (3).

• Breivik, Ø., and Coauthors, 2022: The impact of a reduced high-wind charnock parameter on wave growth with application to the north sea, the norwegian sea and the arctic ocean. Journal of Geophysical Research: Oceans, e2021JC018196.

• Halsne, T., Bohlinger, P., Christensen, K.H., Carrasco, A., Breivik, Ø., 2022: Resolving regions known for intense wave–current interaction using spectral wave models: A case study in the energetic flow fields of Northern Norway, Ocean Modelling,Volume 176.

• Thomas, E. E., Müller, M., Bohlinger, P., Batrak, Y., & Szapiro, N., 2021: A Kilometer-Scale Coupled Atmosphere–Wave Forecasting System for the European Arctic. Weather and Forecasting, 36(6), 2087-2099.

Indices and tables

• Index

• Search Page

• API Reference