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Educators need to be comfortable integrating tools into their own curriculum.
No scaffolding for educators provided, but lots of potential here with real data that real scientists use.
Students will need either prior experience in manipulating and interpreting datasets, or guidance to do so, as none is provided on the site.
This is a reanalysis suite of datasets on weather and climate with a variety of methods to visualize the data - time series graphs, global overlays, etc. - with the capability of using individual datasets or combining them into one visualization.
Note definition of reanalysis: 'Reanalysis is a scientific method for developing a comprehensive record of how weather and climate are changing over time. In it, observations and a numerical model that simulates one or more aspects of the Earth system are combined objectively to generate a synthesized estimate of the state of the system. A reanalysis typically extends over several decades or longer and covers the entire globe from Earth's surface to well above the stratosphere. Reanalysis products are used extensively in climate research and services, including for monitoring and comparing current climate conditions with those of the past, identifying the causes of climate variations and change, and preparing climate predictions.' (from Reanalysis.org)
Comments from expert scientist: This is a tremendous scientific resource that covers both weather and climate and both observed data up to the present and model predictions for a reasonable time span up to the future. This resource serves as a great go-to site for scientific reference and understanding.
Site is complex - multiple datasets provided as well as multiple features with which to manipulate and display the datasets. No direction/support regarding how to use the features, so user needs to experiment and explore.
Excellent visualizations - could be very useful helping students understand how to analyze climate data - good connection to NGSS and Common Core on modeling (math standards) 5b and 5c
Maps and graphics are clean and clear. Variables easy to read.