It cost me quite a lot of time to find a good data source for this topic.
Finally I found a decent data one at Copernicus, though this one only focuses on the Mediterranean sea.
https://data.marine.copernicus.eu/product/SST_MED_PHY_L3S_MY_010_042/description
The files downloaded (for now, manually) are in NetCDF format. The tool below converts these to .csv format. Search for JEM NetCDF to CSV Converter.
Further down, I will show a way to automate this.
The temperature values are in Kelvin. To convert to Centigrade, we have to subtract 273,15. We will do so in the loading workflow.
Below is the first KNIME workflow to load these data into the database.
This workflow loops through the .nc files downloaded from the Copernicus website and converts each file to a .csv file. This is done in the Python Script node.
On this page (work in progress...) I will explain how to set up Python to work with KNIME.
The granularity of the files is quite fine, what I did in order not to load too much data, is only select Integer Latitude and Longitude values. So this will give me a temperature value for each nautical degree which corresponds to 60 Nautical miles (about 111 kms).
I will now load the data for August of each year : 2005- 2025.
Below is the content of the Python script node:
With the workflow below I plot the yearly maximum values. Below that you can see the result.
As you can see, the last years maximum temperatures of over 30 degrees are common.
And here is an example Google Looker report showing the relative maximum Sea Water temperatures in 2025