How to read forecast maps

The forecast map is one of the most important operational products of all – and this lecture shows you how to read one properly.

You’ll see how spatial information is represented using colour shading, contours, vectors, and map projections, and you’ll meet the structure of NetCDF forecast files along with the tools commonly used to view and analyse ocean forecast data – Python, MATLAB, Panoply, ncview, NCO, and CDO.

The heart of the lecture is correct interpretation: reading colour bars, gradients, anomalies, and vectors, and understanding the difference between absolute-value maps and anomaly maps. You’ll see how maps answer questions like where is something happening?, how strong is it?, and how do conditions vary across space? – and how to avoid common mistakes, such as over-interpreting isolated features or misreading colour scales.

The reading that follows puts these ideas straight to work on real forecast maps.