Monitoring Sea Surface Temperature at the global level with GEE
Introduction
The development of Earth Observation and its technological infrastructure has increased considerably in the last decade. Many satellite constellations give open and handy access to their data and researchers can easily access it. For example, Google Earth Engine is a cloud infrastructure that gives access to data from many providers such as Modis, NOAA, ASTER, Lansat, and others, that you can explore and analyze straightforwardly. Give it a look in GEE. In case you want to use the API in Python you can do it with the geemap python library developed by Qiusheng Wu which has wonderful functionalities and can be used as it is in this tutorial.
The infrastructure models are running in near real-time so it is possible to get up-to-date data that helps monitor land and ocean. For this tutorial, we are going to work with the HYCOM dataset which contains a data-assimilative hybrid model that displays the Sea Surface Temperature and Salinity at the global level. The model contains depth values for each temporal layer so users can visualize the ocean at certain depths and dates. The Hybrid Coordinate Ocean Model has been part of many publications and the website contains a lot of documentation about the dataset. If you want to know more I recommend you to give a look at the official website.
App
Get access to the app in the next link:
