I have previously written about this severe cold snap that occurred in the January of 1987 which I think produced the coldest weather for any week in the whole of the 20th century in England and Wales, if not the whole UK. Back when I wrote that original report, which unfortunately I have since deleted, I hadn’t tapped into the MIDAS climate data from the BADC. So here’s an example from the 12th of January 1987 of the richness of the MIDAS temperature data I generated in one of a suite of applications that I developed last year.
As you can see the lowest maximum was recorded at Okehampton in Devon with -8.5°C, but everywhere daytime temperatures where exceptionally low. If you remember the weather situation was an anticyclonic easterly with a pool of sub 496 Dm Arctic air at 500 hpa extending from the continent during Sunday, and progressing eastward during Monday.
A minimum temperature of -23.3°C was recorded in the 09-09 period starting Monday at Caldecott power station of all places. This wasn’t in itself a record breaking temperature. Why? Because although conditions on the ground were perfect for maximum radiative cooling – with many places in eastern England having upward of a 25 cm deep powder snow cover by the end of the day – but the air was far from still and anticyclonic in nature, with a good 30 knot easterly gradient running. So the minimum at Caldecott must have occurred after one of the more heavier snow showers perhaps in a trough, when the sky cleared and the wind managed to fall light for an hour or so.
There is a lot of UK climate data stored at the BADC, the only trouble with that is there’s a lot of data! Data is split the data into yearly chunks for temperature, rainfall, weather etc, probably in a n effort to keep file sizes down. Recent temperature files for example typically weigh in at between 25 and 55 MB, so constructing a LTA for the data required some pretty intensive computer IO. I have an idea to add an extra application to the suite of MIDAS programs I, this one would enable me to extract and create a complete climate record for any climate station, which would include all temperature, rainfall, sunshine and weather data held in the individual MIDAS data files.