Improving reanalysis with offline assimilation

Warning

This document is still under construction.

This is a modernised version of a scientific paper: It shows how to visualise weather reconstructions from the Twentieth Century Reanalysis (version3, 20CRv3), how to validate the reconstructions by comparison with newly-available observations, and how to use the new observations to improve the reanalysis, using an offline version of the ensemble Kalman Filter.

It differs from a standard paper by including video figures, by including many more figures and examples than would be possible in a paper document, and by including all the code and data needed to reproduce or extend it.

• How to replicate or extend this

• Representing uncertainty in weather maps
• Meteorological Data Assimilation for Data Scientists
• DIYA: A module for do-it-yourself data assimilation
• Improving 20CR with observations from the Daily Weather Reports
• Other case studies
• What if: assimilating observations that don’t yet exist
• Improving 20CR with ship observations

• Authors and acknowledgements

This document and the data associated with it are crown copyright (2018) and licensed under the terms of the Open Government Licence. All code included (modules and scripts) is licensed under the terms of the GNU Lesser General Public License.