Rainfall Project – Extending the Climatological Rainfall Observations Series for the UK Using Rainfall Rescue Data

Abstract: The Met Office National Meteorological Archive contains a wealth of historic rainfall observation data in journals and weather logs, extending as far back as the 17th century. In 2020, a concerted effort was made to digitise some of the monthly rainfall data stored in these archives through the Rainfall Rescue project. This project, led by Ed Hawkins with the assistance of around 16,000 volunteers, resulted in over 5 million observations being transcribed, quality controlled and converted into a digital format, which was a remarkable achievement.

A key long-term challenge for the Met Office is how we systematically manage and maximize the use of these new observational datasets and integrate them into our monitoring products alongside existing data sources.  The main objective for this project was to create a more comprehensive monthly rainfall dataset which integrated the digitised Rainfall Rescue data with data derived from MIDAS Open, an open Met Office dataset containing land surface station data back to 1853. An innovative approach was employed to identify the same sites between MIDAS Open and Rainfall Rescue by utilising site metadata and rainfall trend data. A methodology for constructing a new rainfall series for these sites was then developed using this additional source data.

As a result of this initiative, the records of many sites were extended to produce a more complete and robust monthly rainfall series to support climate monitoring and research, with scope to adopt this methodology for other climate variables. I will provide an overview of the newly developed blending method, outline the results, and present the pros and cons of the approach.

Biography: Stephen works as a Scientific Software Engineer at the Met Office. His work includes managing and improving a number of existing UK climate datasets as well as developing new products. These datasets are primarily built on station observations from the Met Office land network sites. Stephen currently maintains the Central England Temperature dataset, the longest continuous monthly temperature series in the world, as well as MIDAS Open, an open dataset of station observations made available publicly via CEDA.