Its been windier than yesterday but nothing at all of note although we did break the date record temp for January at 13.6c not the sort of record i prefer in mid winter though 

Wind and rain every day no frost here in Exeter anyway. 

Temps haven't really fallen at all anyway

I can't see the excitement of wind and rain every day...?

Very stormy south of that squall line,Southend on sea having a very rough time at that the moment hoping people stay safe tonight

https://www.metcheck.com/WEATHER/windtype.asp?V=Z

ps Gusting Violent Storm just south of lizard point 

Significant damage in Slough high street tonight. Pics on Twitter, very lucky if no one injured. 

No ‘gap’ here on West Sussex coast- flipping mental, fences down, branches off, late night trains cancelled. Debris all over the place. 

On another note, many still await the long awaited ‘adjustment’ in model performance stats to change what is still a perfectly normally functioning business as usual over Christmas:

https://www.emc.ncep.noaa.gov/gmb/STATS/html/new_acz6.html

Many more of us await you giving up repeating yourself about model performance stats and Christmas like some kind of broken record.....

Agreed. I posted about it just after Christmas, too, but as usual WM ignored it. That post is still to be found on this thread too!

Incidentally, via Slashdot, Google has a new weather model that doesn't use physics. Wonder how that'll do? From Slashdot:

A research team at Google has developed a deep neural network that can make fast, detailed rainfall forecasts. Google says that its forecasts are more accurate than conventional weather forecasts, at least for time periods under six hours. Ars Technica reports: The researchers say their results are a dramatic improvement over previous techniques in two key ways. One is speed. Google says that leading weather forecasting models today take one to three hours to run, making them useless if you want a weather forecast an hour in the future. By contrast, Google says its system can produce results in less than 10 minutes -- including the time to collect data from sensors around the United States. A second advantage: higher spatial resolution. Google's system breaks the United States down into squares 1km on a side. Google notes that in conventional systems, by contrast, "computational demands limit the spatial resolution to about 5 kilometers."

Interestingly, Google's model is "physics-free": it isn't based on any a priori knowledge of atmospheric physics. The software doesn't try to simulate atmospheric variables like pressure, temperature, or humidity. Instead, it treats precipitation maps as images and tries to predict the next few images in the series based on previous snapshots. It does this using convolutional neural networks, the same technology that allows computers to correctly label images. Specifically, it uses a popular neural network architecture called a U-Net that was first developed for diagnosing medical images. The U-net has several layers that downsample an image from its initial 256-by-256 shape, producing a lower-resolution image where each "pixel" represents a larger region of the original image. Google doesn't explain the exact parameters, but a typical U-Net might convert a 256-by-256 grid to a 128-by-128 grid, then convert that to a 64-by-64 grid, and finally a 32-by-32 grid. While the number of pixels is declining, the number of "channels" -- variables that capture data about each pixel -- is growing.

The second half of the U-Net then upsamples this compact representation -- converting back to 64, 128, and finally 256-pixel representations. At each step, the network copies over the data from the corresponding downsampling step. The practical effect is that the final layer of the network has both the original full-resolution image and summary data reflecting high-level features inferred by the neural network. To produce a weather forecast, the network takes an hour's worth of previous precipitation maps as inputs. Each map is a "channel" in the input image, just as a conventional image has red, blue, and green channels. The network then tries to output a series of precipitation maps reflecting the precipitation over the next hour. Like any neural network, this one is trained with past real-world examples. After repeating this process millions of times, the network gets pretty good at approximating future precipitation patterns for data it hasn't seen before.

GFS has high pressure over the UK to Tue 21st (once this week's rubbish has gone) but then maintains HP close by till Tue 28th when a trough drifts in from the N Atlantic.

BBC last night was going for full on zonal stuff  from Wed 22nd instead of maintaining the HP.

ECM takes a middle position as does the Jetstream which is looping around early next week to support high pressure over UK around Mon/Tue 20th/21st but soon back to strong westerly, then weaker a week later and diving well south for a while.

GEFS has rain on 17th (mostly in S) then dry to 25th; cool at first then milder for a while from 21st (a day or two earlier in N) until the usual scramble sets in.

Nothing generally cold on the FI postage stamps out to T+384, so I'm pinning my hopes for a cold spell on the cold air creeping across the NE Atlantic in week 2 and then developing http://www.wxmaps.org/pix/temp4

Sounds like good old-fashioned pattern recognition, souped up a bit for short time spans. I'm sure Google will be working on it but will the technique be extendable beyond, say, 24hrs?

With that sort of setup, it wouldn't therefore surprise me if the south of England gets virtually all of any frost which is going, whilst we in Scotland continue to be stuck under a mild SW air flow. That would put us into even more of a winter borefest with almost constant grey skies, and with nothing which is even remotely interesting in terms of our weather, actually happening. Sheltered eastern parts of Scotland might see some breaks in that cloud, but this would only be accompanied by temperatures rising well into double figures due to the Foehn Effect.

EDIT: Oh, why bother. Welcome to the ignore list.

Thanks. It's good to read a succinct summary of where we stand every morning.

I will welcome the arrival of high pressure to settle the weather down for a while. Where it goes after that is up for debate but as nsrobins mentions it is hard to bet against a sinker with zonal conditions re-establishing.

I hope those pinning their hopes on the favourable MJO phase 7 are not overestimating any potential impact it has on our weather once the models pick up the influence.

Malcolm
Wakefield & Gothenburg, SWE

Seconded, and a big to DEW for providing it.

Control goes for a SSW at +300:

Operational - Is going for a slight SW post +300 but does eventually get there...!?

It does eventually get there end of run:

Well at least in Autumn there was snow in Devon  - whilst I was away on 13th November. Could have had my first white birthday since Krakow, Poland on 13th Nov 2007.

Many parts of the Moors incl Princetown had between 2-3cms of snow and there was a dusting of wet snow over Okehampton, sleet fell in Crediton and wet snow too.

https://www.cornwalllive.com/news/heavy-snow-fall-devon-live-3534924

Good to see GFS trying to show an "omega" high off to the west of the UK thus bringing the Atlantic flow to a dead stop, that's exactly what we need to dry things up but still keeping temperatures close to seasonal norm. Let's see if the ECM come up with the same idea. 

Tally non of those charts show an SSW. They show some warming at 10hPa but that’s not an SSW. 
The zonal wind vectors do look like slowing in the next few weeks but whether it’s enough to induce a technical SSW is another matter. 
http://weatheriscool.com/prod/interactiveTserie.html

Sadly I don't think it will hold: the pattern suggests the northern arm of the jet is going to flatten things again.