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Comment by elil17 | Hacker News Reader

Like many other people are commenting, I have subjectively felt that rain forecasts have gotten worse. I can think of two theories that could explain this. I'd be curious to hear from someone more knowledgeable if any of them are right or plausible.

1. High frequency 5G has thrown off rain forecasts in urban areas. Average prediction accuracy has still improved because rural/suburban areas don't have high frequency 5G.

2. The weather app now shows rain forecasts in time blocks as small as 15 minutes, even though predictions this granular are still inaccurate. This has inflated our expectations for forecast accuracy.

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A theory I've been entertaining lately is that the raw engineering of the weather forecasts has indeed gotten better, but it has been offset by the clickbait-driven need for weather forecasts to declare everything to be the Worst Thing Ever, Click Here To Not Die. Snow storms that would have in my youth been a medium experience hardly worthy of note get their own names and days of breathless pre-coverage from the weather channels nowadays.

The net is the improved raw accuracy of the weather forecast is offset by the difficulty of reversing the clickbait layer slathered on top.

I would guess it is mostly down to option 2, coupled with the fact that aspects such as precipitation onset are possibly not something that actually has improved much: the examples given are hurricane tracks and atmospheric pressure which don't obviously couple tightly to when it starts raining.

An area has to be extremely densly trafficked before high frequency 5G is deployed. And even then, the whole point is to minimize broadcast range to avoid interference.

Further, it's only the upper range of high frequency spectrum that's being used (not sure who owns it) so it's not even every carrier that could interfere.

Finally, the most powerful radars are transmitting in the kilowatts range of output. It's hard for me to imagine that the microwatt output of cellphones are often the cause of radar interference.

How does mm wave 5G effect forecasts? Interfering with weather radar?

23.8-gigahertz 5G signals can look like water vapor to the instruments on weather satellites.

Another possibility from another top-level comment

"I remember reading in The Signal and The Noise* that people _think_ that forecasts are bad if it rains, but the chance of rain was reported as below 50%. Getting rain when the forecast told you there would probably not be rain is annoying; getting a sunny day when the forecast predicted likely rain is a pleasant surprise. To get what people judge to be a ‘good forecast’, the chance of rain has to be adjusted to be wildly too high - so that’s what consumer-focused forecasters do."

https://news.ycombinator.com/item?id=39684844

Learning to read radar is phenomenally helpful in determining whether or not it will rain. It's not very difficult either.

A few years ago I was able to stop my friend's outdoor wedding (on the terrace as opposed to the hall, the venue had both ready) from getting rained out by reading the radar and catching a small pocket storm that had formed and coming right towards us. Sure enough it down poured, but everyone was inside for the ceremony. Reading just the weather report, there wasn't even rain forecasted.

Where can one learn to read radar, sounds fun and useful!

Short-term forecasts (1-2 days) seem more accurate than ever. However, weather as a business has meant a race at both ends of the forecast spectrum. Apps now offer minute by minute forecasts on the one hand or 10 and 15 and even 90 day forecasts on the other. Neither of those forecasting models are anywhere near ready for prime time but there is a market demand for them, so they get put out there anyway.

(2) is a big ol' bingo. There was a race towards the bottom line of higher spatial and time resolution over the past 5 years (claims along the lines of "higher resolution means higher accuracy!"), which led to an awful lot of products that are nothing more than naive interpolations of coarser data. So couple the perception of "better"/"more accurate" products with a wholly insufficient technical approach to realizing this and you have a perfect storm for end users to feel that weather forecasts are getting worse. They just over-promised and under-delivered because many people who entered the field from outside of it completely underestimated how hard it is to push weather forecasting technology forward.

(1) is irrelevant for weather forecasting.

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