u/4billionyearson

A couple of months ago I posted here when the UK announced approval for plug-in solar.

Since then I've been tracking the regulations, retailers and pricing almost daily. Thought it was worth an update because things have moved on significantly ...

You can build a complete 465W/800W setup for £260/£370, all from City Plumbing.

Here’s the breakdown:

• 1 or 2 × DMEGC 465W G12 All Black Solar Panel - £120/£240 https://www.cityplumbing.co.uk/p/dmegc-465w-g12-all-black-solar-panel/p/231059 (more options available...you can plug 2 into the microinverter)
• Hoymiles HiFlow 800W plug-and-play microinverter with UK plug - £120 ... https://www.cityplumbing.co.uk/p/hoymiles-hiflow-800-microinverter-with-uk-plug-and-play-cable-wifi-bluetooth/p/298817 (order now, collect on 1 July)
• MC4 cables + basic mounting, approx. £20

Total: £260 for 465W or £370 for 930W, limited to the 800W legal limit by the inverter. Lean the panels against a fence or mount on your shed roof/balcony ... job done.

The fact that City Plumbing (a big player in the solar market) is now stocking a specific UK plug-in inverter (and a wide range of panels) is a great sign for DIYers.

It's not quite legal yet ...

BS 7671 Amendment 4 went live on 15 April. That’s the wiring regs update that formally recognises plug-in solar in the UK. But the BSI product standard, the bit that certifies specific kits as compliant, isn’t expected until mid-July. So technically no kit is formally certified yet, though several are already being sold in anticipation of it. You also still need to notify your DNO within 28 days of installing (free G98 form, no approval required, just a notification).

I ended up building an online guide that updates daily because there still isn’t a single place covering all this properly. It tracks the regulations, G98/DNO changes, mainstream products, and has a postcode payback calculator and a landlord letter template for renters (they can do this too). It also goes into more detail about using batteries ... the new regulations allow them to be used with solar, or also without solar, for time shifting on a smart tariff.

https://4billionyearson.org/plug-in-solar-uk

Hope this is useful.

The SNU deep learning model and the IRI dynamical ensemble are currently giving very different pictures of where this El Nino is heading, and the difference is large enough to matter for real-world impacts.

The SNU CNN model (Ham et al. 2019, Nature) was specifically designed for long-lead ENSO prediction up to 18-24 months out, where traditional dynamical models historically struggle. Its April 2026 forecast projects a significantly stronger El Nino peak in 2026-27 than the IRI/CCSR dynamical model mean. At the top end of the SNU projection you are looking at drought conditions across Australia and Indonesia, monsoon disruption across South and Southeast Asia, and flood risk across East Africa and South America on a scale closer to 1997-98 than to 2015-16. The dynamical ensemble mean tells a more moderate story.

Since February 1, 2026, NOAA switched its official Nino indices from traditional SST anomalies to relative anomalies, where the tropical mean SST departure (20S-20N) is subtracted out. The reasoning is sound - the atmosphere responds to gradients not absolute temperatures, and the relative index aligns better with observed rainfall and circulation anomalies. But the IRI forecast plume - 26 dynamical and statistical models - still outputs traditional anomalies.

So at the moment ...

• NOAA's official Nino 3.4 monitoring value is around +0.4°C (relative)
• The same week in the IRI plume reads +0.9°C (traditional)
• The IRI dynamical mean peaks around +2.1°C for OND 2026 in traditional terms, which is roughly +1.6°C in relative terms - the difference between record-breaking and strong-but-not-exceptional headlines

I've been tracking the weekly Nino 3.4 data alongside both forecast systems and this inconsistency became hard to ignore. A few questions for people who work with this more than I do ...

1. How do you assess the SNU model's real-time skill given it has only been live through a limited number of ENSO events since 2019 - is the current divergence from the dynamical ensemble meaningful or within expected spread?
2. Should the IRI plume start presenting outputs in relative terms to match NOAA monitoring, or does that break too much of the historical verification framework?
3. Is there a clean way to compare forecasts across the traditional vs relative boundary when looking at historical analogues?

Happy to share the tracker link if useful, but mainly interested in how others are thinking about the model divergence and what it means for impact forecasting right now.

The latest Niño 3.4 sea surface temperature anomaly is now +0.9°C, which puts it clearly into El Niño territory and still trending upward.

That in itself isn’t unusual at this stage, but what’s interesting right now is the spread in forecasts.

– Traditional dynamical (physics-based) models are indicating a developing El Niño

– A deep learning model (SNU, published in Nature in 2019) is currently projecting a much stronger event ...

https://preview.redd.it/eycxsilokbzg1.png?width=1124&format=png&auto=webp&s=050445a19845fb4a36b6c000723e8ccad1b71aa8

That divergence caught my attention because ENSO onset is one of the harder things to predict, and the SNU model showed higher skill in hindcasts, particularly at longer lead times.

If the stronger scenario plays out, it would likely amplify typical El Niño impacts:

– increased drought risk in parts of Australia/Indonesia

– heavier rainfall risk in parts of South America and East Africa

– an additional push on global temperatures

I’ve been tracking the weekly Niño 3.4 updates alongside both forecast systems here:

https://4billionyearson.org/climate/enso

Curious how others here view the current signal - does the model divergence feel meaningful yet, or still within normal spread at this stage?

ENSO is currently in neutral (ONI -0.16°C), but the coastal Pacific is already running hot - Niño 1+2 is at +1.80°C this week. Models are converging fast: NOAA puts El Niño probability at 61% by May-Jul, climbing to 93% by Oct-Nov-Dec, with a dynamical-model average peak of +2.1°C. This is strong-to-super territory.

Every El Niño now releases its heat onto a baseline already 1.3°C above pre-industrial. The 2023-24 event (peak ONI +2.0°C) made 2024 the first calendar year above 1.5°C. A comparable or stronger event in 2026-27 would push that further.

I've been building a free ENSO tracker that pulls together the four main indicators (Niño 3.4, ONI, MEI v2, SOI) with the NOAA forecast, regional impact cards for 20+ regions, and the history of major events back to 1982.

Sharing it here in case it's useful ... https://www.4billionyearson.org/climate/enso

https://preview.redd.it/o51twscxjxxg1.png?width=1342&format=png&auto=webp&s=9be11f0780050e1ceb598e844d03480fe659b99d

ENSO is currently in neutral (ONI -0.16°C), but the coastal Pacific is already running hot - Niño 1+2 is at +1.80°C this week. Models are converging fast: NOAA puts El Niño probability at 61% by May-Jul, climbing to 93% by Oct-Nov-Dec, with a dynamical-model average peak of +2.1°C. This is strong-to-super territory.

Every El Niño now releases its heat onto a baseline already 1.3°C above pre-industrial. The 2023-24 event (peak ONI +2.0°C) made 2024 the first calendar year above 1.5°C. A comparable or stronger event in 2026-27 would push that further.

I've been building a free ENSO tracker that pulls together the four main indicators (Niño 3.4, ONI, MEI v2, SOI) with the NOAA forecast, regional impact cards for 20+ regions, and the history of major events back to 1982.

Sharing it here in case it's useful ... https://www.4billionyearson.org/climate/enso

https://preview.redd.it/gt1afg74mvxg1.png?width=1460&format=png&auto=webp&s=f8301e5ed1536bf3213da4df39c32791a57da1e7

I came across this paper, published by Google on 21 March ... Agentic AI and the next intelligence explosion

I think it has real significance to the idea of AI consciousness.

The researchers found that Agentic AI is not 'thinking longer' to solve reasoning problems, but found strong evidence of multiple distinct cognitive perspectives being argued, questioned, verified, and reconciled in order to solve problems inside a single artificial mind.

The AI models were not trained to do this, they seem to have discovered it on their own. It is described as being emergent. I realise this sounds far-fetched, but it is mainstream published research.

This certainly doesn't solve The Hard Problem, but it suggests that AI has moved beyond flat, linear computation, perhaps creating a "Society of Thought". There may be some form of continuity developing.

What do you make of all this?

If interested, I have written a blog post looking into the research in more detail (free, no ads etc) ... Forget the Singularity: Google’s New Research Says the Future of AI is a Social Explosion