Earthshine
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Over 10 hours of sunlight here in Exeter tomorrow with sunset at 17:31. Definitely noticing the sun getting stronger tomorrow with beautiful sunny skies and forecast temperatures up to 14°C. The sun is climbing higher now, up to 27° above the horizon. Looking forward to that first 20°C day now
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Metwatch Interesting how 2021 makes it there too!
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Met4Cast This is another huge nail in the coffin for those few still banging on about solar activity causing warming. If the sun was outputting more energy the entire atmosphere would be warming. The fact we can observe the stratosphere in fact cooling is a sure sign of increasing carbon dioxide in the lower atmosphere.
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Metwatch Very interesting! Going by highest temperatures on record for each country is also pretty fascinating:
England: July 2022
Wales: July 2022
Scotland: July 2022
Northern Ireland: July 2021
Record high minimums:
England: July 2022
Wales: July 2022
Scotland: July 2019
Northern Ireland: August 2001
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Derecho A lot of NWP is parameterised where the scale of events is just too small to capture in the model (e.g. really local convective events). In theory AI isn't really limited to a grid, I've seen neural fields allow variables to be mapped to arbitrary resolution (e.g. your neural network maps x, y, z coordinates f(x,y, z) --> t,p,q with no reference to an actual grid). Probably won't work in NWP, but we already can already see upscaling of precipitation using AI show encouraging results: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2022MS003120
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Frigid Life in the UK really is relentless
a winter supposedly posed to bring cold weather ended up almost seeing 20°C being reached in Scotland.
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Granted I know almost nothing about this, but it would be super interesting if there was a reanalysis study to see if MJO/AAM/etc. predictions do have some medium range skill and how good they are. It would probably be a huge undertaking, but say we took the MJO forecasts from previous spells that preceded high latitude blocking events. What kind of forecasting skill could we see? I'm sure the vast density of information in the ERA5 could be used to create a pseudo forecast perhaps. It would be interesting to try to quantify how useful these driver forecasts are in a historical setting, which might inform us on how to use them now.
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Relativistic Thanks! It's an interesting problem. Really the model is trained to minimise the difference in variables between the ERA5 dataset and it's own output (Pangu is four surface and 5 upper air variables - MSLP, T u, v winds + mixing ratio for upper air variables on 13 pressure levels). It infers the physics on how these variables interact with zero knowledge of the known physics, something I find extraordinary that it works!
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Mike Poole You're exactly right. There is no inherent knowledge of physics, only inferred from the ERA5 training data. I'm amazed it works, it seems such an ill-posed problem yet here we are. On the problem of not respecting physical laws, this is a problem because the atmosphere is chaotic and if you aren't conserving energy the intensity of storms is underestimated. We saw this with AI forecasts for Storm Ciaran which were weaker than the physics-based IFS forecast.
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The PIT That's actually a problem with "AI" models. They are trained to minimise the absolute error between the output and the training reanalysis dataset. When used operationally, the output that is an optimum solution is a "blurred" forecast with no extremes at longer lead times. You can actually see the kinetic energy just randomly drop away. I've applied for a grant to work with a software engineer to hopefully incorporate physical constraints into the training of these models. Hopefully then the output will be constrained to not only fit the observational data, but to actually force it to conserve kinetic energy, mass, etc. These data-driven models are the very first generation of operational models. I would be EXTREMELY hesitant to say that they will never overtake classic physics based models. The rate of progress has just exploded - and these are basically equivalent to the very first generation of classic NWP models. Personally I think the biggest constraints to better weather forecasts at the moment is a lack of observations - satellites are great, but the vertical resolution of sounders is seriously lacking.
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A very good summer that is rarely spoken about. Every month was significantly warmer than average. Here's the season and monthly maximum CET values:
Summer: 22.2°C (6th hottest on record)
June: 21.3°C
July: 22.0°C
August: 23.3°C
There were unfortunately drought conditions. Every day from the 24th July to the 28th August recorded a maximum CET of at least 20°C.
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lassie23 I wouldn't be so sure, the AIFS has recently been updated by the ECMWF and has skill just as good as the physics-based IFS using attention graph neural networks: https://www.ecmwf.int/en/about/media-centre/aifs-blog/2024/first-update-aifs
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I would absolutely not worry about what this summer will be like - that goes for both warm weather and cool weather fans! Many were saying 2022 will have a mediocre August because of La Nina - ended up being the third warmest on record. Last summer was supposed to be a summer of heat plumes - none except in September! Personally I'll be concerned when we get to June and we see zero warm ensemble members
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My ideal climate would be 32°C during the day and 20°C at night, thinking somewhere like a Carribbean climate. I love warm nights where I can just sit outside and chill. I do struggle when temperatures get close to 40°C though.
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- Popular Post
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A March like 2022, an April like 2020 and a May like 2018/2020 would be fantastic. I'd like to see gin blue skies and bone dry conditions in May, a bit like 2020 (picture below).
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Potential for exceptionally mild end to the month. Long way off of course but quite a few of these are very February 2019-esque
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3.7°C and 60 mm please
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Word of caution - in the absence of a strong driving signal, NWP models will often drift towards the climatological mean (background covariances in data assimilation will often penalise large departures from climatological mean).
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1 minute ago, Met4Cast said:
I've had this discussion with senior Mets before.
The main reason is that it's difficult to know air thickness without direct observations or model data, the analysis charts are primarily drawn up from satellite imagery which obviously doesn't show DAM lines.
So, to avoid the analysis charts importing too much of a "forecasting" aspect they leave them out.
I'm surprised they are predominantly done with satellite data, I would have thought they would have been created using the analysis (i.e. all assimilated observations in that time window).
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13 hours ago, Roger J Smith said:
Analysis of scoring for recent normals and our consensus
_________________________________ Forecasts _______________ Errors ___________ Rank _______
"Robot" Forecaster _________ CET ___ EWP ___________ CET __ EWP ____ CET __ EWP
1981-2010 average DEC ___ 4.5 ____ 97.4 ____________ +1.1 __-4.6 _____ 55 ___ 2.3
1981-2010 average JAN ___ 4.4 _____ 93.0 ____________ -0.8 __ -4.8 _____ 40 ___ 18.5
1981-2010 average FEB ___ 4.4 _____ 66.5 ___________ -2.1 __ +52.5 ____ 40 ___ 37.0
1981-2010 average MAR ___6.6 _____ 71.5 ___________ -0.4 __ -65.3 _____13 ___17.2
1981-2010 average APR ___ 8.5 _____ 64.8 ___________ -0.2 __ -12.1 _____11 ___ 23.2
1981-2010 average MAY __11.7 _____ 63.6 ___________ -0.8 __+20.1 _____50 ___ 24.6
1981-2010 average JUN ___14.4 _____ 66.3 ___________-2.6 __+16.3 _____44 ___ 44.2
1981-2010 average JUL____16.6 _____ 67.3 ___________+0.5 __-62.2 ______ 6 ___ 28.4
1981-2010 average AUG __ 16.5 _____ 75.6 ___________ 0.0 __ +0.6 _______3 ___ 0.8*
1981-2010 average SEP ___ 14.0 _____ 77.2 ___________-3.0 __-13.8 ______58 ___5.5
*rank 0.8 for AUG EWP was better than all forecasters (error 0.6, their low error 2.0). For CET I rounded 16.45 (1981-2010 value now in v2.0.1.0) up to 16.5. Even so, 1981-2010 was clearly a very accurate forecast of Aug 2023.
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1991-2020 average DEC ___ 4.8 ____103.6 ____________ +1.4 __+1.6 _____ 63 ___ 0.4
1991-2020 average JAN ___ 4.7 _____ 94.2 _____________ -0.5 __ -3.6 _____ 28 ___ 17.8
1991-2020 average FEB ___ 5.0 _____ 72.4 _____________ -1.5 __ 58.4 ____ 39 ___ 40.3
1991-2020 average MAR ___6.7 _____ 65.4 _____________ -0.3 __-71.4 ____11 ___ 30.6
1991-2020 average APR ___ 9.0 _____ 63.2 _____________ +0.3 __-13.7 ____16 ___ 25.1
1991-2020 average MAY ___11.9 ____ 62.7 ______________-0.6 __ 19.2 ____42 ___ 21.1
1991-2020 average JUN ___ 14.6 ____ 70.5 ______________ -2.4 __20.5 ____ 50 ___ 47.2
1991-2020 average JUL ____16.8 ____ 72.0 ______________ +0.7__-57.5_____10 ___ 22.0
1991-2020 average AUG ___16.6 ____ 82.3 ______________+0.2 __ +7.3 _____ 6 ____ 9.6
1991-2020 average SEP ___ 14.2 ____ 76.0 ______________-2.8 __-15.0 _____ 56 ___ 6.0
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1992-2021 average DEC ___ 4.9 ____105.5 _____________ +1.5 __+3.5 _____ 65 ___ 0.9
1993-2022 average JAN ___ 4.7 _____ 95.4 _____________ -0.5 __ -2.4 _____ 28 ___ 13.5
1993-2022 average FEB ___ 5.1 _____ 74.9 _____________-1.4 __ +60.5 ____ 36 ___ 41.4
1993-2022 average MAR ___ 6.7 _____63.6 _____________-0.3 __ -73.2 ____ 11 ___ 32.7
1993-2022 average APR ____8.9 _____59.8 _____________ +0.2 __-17.1 ____ 11 ___ 32.2
1993-2022 average MAY ___11.9 ____ 66.6 _____________ -0.6 ___ 23.1 ____ 42 ___ 29.8
1993-2022 average JUN ____14.7 ____ 69.5 _____________-2.3 ___ 19.5 ____ 49 ___ 45.8
1993-2022 average JUL ____ 16.9 ____ 70.5 ____________ +0.8 __ -59.0_____ 14 ___ 22.7
1993-2022 average AUG ___ 16.6 ____ 79.9 ____________ +0.2 __ +4.9 ______ 6 ____ 2.9
1993-2022 average SEP ____ 14.3 ____ 75.9 ____________ -2.7 __ -15.1 _____ 56 ___ 6.1
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consensus DEC ____________ 3.5 ____ 63.0 ______________ +0.1 __-39.0 _____ 04 __ 39.0
consensus JAN _____________5.1 ____ 99.5 _______________-0.1 __ +1.7 _____ 1.5 __ 5.9
consensus FEB ____________ 5.4 ____ 65.0 _______________-1.1 __ +51.0 ____ 29 ___ 31.0
consensus MAR ___________ 5.9 ____ 67.0 _______________-1.1 __ -69.8 ____ 27 ___ 25.0
consensus APR ____________ 9.0 ____ 65.0 _______________+0.3 __-11.9 ____ 16 ___ 20
consensus MAY ____________12.3 ___ 65.0 _______________-0.2 __ 21.5 _____ 23 ___ 25
consensus JUN _____________15.4 ___ 50.0 _______________-1.6 __ +1.2 _____26 ___ 11
consensus JUL _____________ 17.6 ___ 68.0 ______________ +1.5 __-61.5 ____ 30 ___ 27
consensus AUG ____________16.8 ___ 82.7 ______________ +0.4 __ +7.7 ____ 16 ____10
consensus SEP _____________15.5 ___ 56.0 ______________ -1.5 __ -35.0 ____ 30 ____26
=======================
1981-2010 mean of 10 mo __ ___ ___ _____ ________________1.15 __24.59 ___ 33 ___ 4.1
1991-2020 mean of 10 mo __ ___ ___ _____ ________________1.05 __25.90 ___ 34 ___ 6.1
1993-2022 mean of 10 mo __ ___ ___ _____ ________________1.04 __26.95 ___ 34 ___ 7.9
consensus mean of 10 mo __ ___ ___ _____ ________________0.79 _ 28.99 ____ 22 __ 17.2
(note mean of errors is mean of absolute errors, not actual errors)
(mean of actual errors is "bias" of forecasts and is around -1.0 for 1981-2010 and -0.7 for 1991-2020, and is currently -0.33 for our consensus, meaning on average our consensus forecasts were 0.33 below outcomes but normals were 0.7 to 1.0 below outcomes ... it's a different measure of consensus being a bit better compared to normals).
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ANALYSIS: For CET, September widened gap between consensus and normals, as our consensus gained more ground and moved into a statistically significant position relative to the random aspect of normals. For EWP, the trend moved in opposite direction with normals gaining further on their August advantage over consensus. So in other words, most of us are making skilled forecasts of CET but not EWP where using normal values would improve our scores. In fact, only top 3 or 4 EWP forecasters are improving on normals, while top two-thirds of the CET contest field achieve at least some improvement over normals.
That's amazing, won't be long until the 30 year mean for July gets to 17°C I reckon.
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PanguWeather looks like maintaing a pretty mild feed out until second half of next week. Very warm this weekend. Each model run is about 10,000 times cheaper than the equivalent using a full-physics NWP model. I reckon we will see enormous ensemble runs using these, 10,000 ensemble members for the price of a single ensemble member from the ECMWF or GFS!
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Makes me laugh when people say we can't reach X temperature despite it only being 1-2C off what we've seen in climatology. Have we truly sampled the entire distribution of possible temperatures in the UK records? Almost certainly not. Especially since the mean (and likely variance, although it probably isn't a normal distribution anymore) has shifted dramatically in the last few decades. Even if the mean hasn't shifted, we would probably need thousands of years to properly sample the extreme ends of the UK climate distribution (ignoring the fact that the climate rarely stays the same over those kinds of time periods)!
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General summer chat
in Spring Weather Discussion
Posted
Global temperatures just keep getting higher and higher. This month has already seen the longest streak of +2°C above pre-industrial on record. There is far more energy to work with than in previous years. If we do get a favourable synoptic set up this year I would say this year would be in for a good chance of seeing more extraordinary warmth. Even last year, which was pretty lackluster for warmth, still saw two 17°C CET months. It'll be very difficult to get anything very cool with so much warmth around.