Friday 5th August
The thick black clouds, from the back edge of the weather front, rolled away just before 08.00 on Thursday that left an interval of blue sky before brief showers arrived just after 09.00 that amounted to 1.0mm. Thereafter the day was dry with the thermometer edging upwards to reach a maximum of 19.1C at 14.45 in warm sunshine, being 0.1C above average. Although the peak UV level is now at a ‘Moderate’ level the peak solar of 909W/m2 was the second highest this month.
The temperature dropped steadily away overnight that gave a minimum of 9.3C at 04.24 being just above average at +0.6C. The recent wet weather, resulting in high humidity, combined with the lowest minimum temperature this month, produced radiation fog in the River Og valley, observed just after sunrise, that had all but evaporated by 07.00 as the sun rose higher and began to lift the temperature, which had reached 13.4C by 08.00.
Friday gave us a bright start with sunshine that has the promise of a dry, fine day ahead.
As the depression eased away northwards on Thursday, an anticyclone centred over the Azores had been steadily building over the UK with a significant rise of 17mb during the past twenty-four hours and continues to rise steadily. This high pressure will give us a couple of warm, dry days ahead. As it eases away eastwards over the Continent on Saturday this will allow the airstream to travel around its southern flank, over the warm Continent, before arriving with a steady flow of very warm air on a southeasterly flow that will result in the thermometer rising well above average. It will also keep at bay for a day a deep depression closing in the UK from the eastern Atlantic that will bring more cloud on Sunday but probably stay dry.
A recent Met Office press release stated that ” Machine Learning-based weather models have the potential to revolutionise global seasonal forecasting, according to new Met Office-led research. According to new research, the ML model, known aa ACE2, demonstrates comparable (though lower) performance to existing methods, with significantly less computing power required. They go on to state that “We’ve found that ACE2 shows skills comparable to existing physics-based methods, which could open up new opportunities on generating more detailed and accurate forecast at a seasonal range.”