Ocean Model Data

AdriaClim Project: Climate change information, monitoring, and management tools for adaptation strategies in Adriatic coastal areas.

CMEMS Ocean Model Data Post-Processing:

You can download an Ocean Product from CMEMS: Then you can use the following Jupyter notebooks to manipulate the files (or download the ocean_data.nc):

. Temperature_time_series.ipynb shows an CMEMS Ocean file in time series in a fix point.

. "interpolation.ipynb" explaines how to do a Vertical profile interpolation for selected levels with using numpy.interp function.

. "temperature_by_depth.ipynb" shows a graph to see the Vertical Profondity in the ocean_data.nc file through xarray function.

. "read_file_temperature.ipynb" describes the statistics of the 2020-11-16T12_00_00_Daily_temp_2020_AdriaticSea_Z10_CF.nc file.

In the following scripts there are examples of ocean data visualization by using GeoCAT module and Cartography library.

Reading file is : 2020-11-16T12_00_00_Daily_temp_2020_AdriaticSea_Z10_CF.nc post-processed CMEMS Ocean file.

. "Mediterranean_Sea_Physics_Analysis_and_Forecast_Ocean_Product_Temperature_at5m.png" is the result of the GeoCAT visualization example through "cmems_Geocat_visualization_temperature.py"

. The visualization by using Cartography library has been shown through "cmems_cartography_visualization_temperature.ipynb"

OCEAN COLOUR WITH SENTINEL-3 OLCI

. S3 Data can be downloaded from ESA SciHUB then, need to select the area of interest and time covarage. In this case the product name is S3A_OL_2_WFR on 2020-06-28. Once finish the download, select variable CHL with NN (Neural Networks). The "geo_coordinates" cointains DEM corrected latitude information for the CHL_NN. S3 can be processed in the same way through SNAP.