
Advances in Weather Prediction - ALee
http://science.sciencemag.org/content/363/6425/342
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Tepix
One (rather easy?) thing I'd like to see in weather forecast apps is a
confidence score.

I know that sometimes the weather is hard to predict. Right now I can't tell
by looking at the weather forecast how confident they are. If the different
weather models give significantly different forecasts, the confidence score
should reflect it.

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evandijk70
The Dutch weather forecast has an 'expert' forecast that includes confidence
bands, see:

[https://www.knmi.nl/nederland-nu/weer/waarschuwingen-en-
verw...](https://www.knmi.nl/nederland-nu/weer/waarschuwingen-en-
verwachtingen/weer-en-klimaatpluim)

The page is not very popular though

~~~
taejo
That's great, I would love it if there was something like that that covered a
wider area.

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mehrdadn
How good is weather prediction for other people? Is it actually accurate for
you? Are even the _current conditions_ accurate for you? I use Weather
Underground, and a few weeks ago in the Bay, here are just a couple of the
things I remember observing (out of the _many_ wrong predictions): (1) One
afternoon I was told there would be rain in 5-6 hours, then a couple hours I
was told there would be none. (2) I started getting soaked while walking
outside, and I checked the _current conditions_ and was informed it is in fact
not raining and there is no upcoming rain either. These were despite the facts
that the weather stations were < 1 mile away for me and the conditions
persisted for a fair bit (i.e. it wasn't just a random 2-minute shower).

~~~
minimalist
If you are in the United States, you may be interested in the scientific
forecaster discussions produced by your local NWS office. They provide more
insight into forecast confidence and general regional dynamics. Theyre
produced several times a day and are often quite fun to read.

Its amazing how far we have come in weather prediction. A few decades ago,
5-day forecasts did not exist and now we get 10-day forecasts that are
reliable enough that we take it for granted.

In my experience, nothing beats getting the forecast straight from the horses
mouth (NWS that is). Some companies are notorious for producing 30+ day
forecasts, which cant have any meaningful levels of skill.

I never understood why NOAA/NWS didnt just create their own mobile app. I use
Wx[0], which parses NWS data directly and can be found on f-droid.

[0] [https://gitlab.com/joshua.tee/wx](https://gitlab.com/joshua.tee/wx)

~~~
mehrdadn
Interesting... do you see the NWS forecasts being more accurate then
Weather.com/Weather Underground? It always felt to me like the former was
(basically/effectively) a low-pass-filtered version of the latter, not
actually any more accurate, but I have't really compared them that carefully.

~~~
Donald
The NWS produces expert commentary (aka "forecaster's discussion") that can
explain the deviations from forecasted weather. For example, there is a
stalled weak cold front over the US right now. Many areas are getting variants
of "Though not currently included in our forecast, very minor rain chances
could return on Wednesday with models indicating some eastward movement of the
ridge and an increase in PWAT values" based on the underlying uncertainty
behind where exactly this frontal system will stall out.

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ncmncm
Not widely publicized is that 5G cellular is going to eliminate one of the
primary data inputs that have made weather prediction successful.

The US FCC decided, on their own, that this was not an important problem,
compared (most likely) to the amount of money to be made building out 5G.

~~~
halter73
Let's stick with facts instead of fear mongering.

I dislike Ajit Pai as much as the next person and wish he had heeded NASA's
request to delay the 5G role out. That said, it's not a forgone conclusion
that 5G will significantly interfere with let alone eliminate the ability of
radio spectrometers on weather satellites to measure water vapor using the
23.8 GHz band.

The new FCC UMFUS regulations that govern 5G require require signals to use a
set of frequencies all of which are greater than 24 GHz.

That said, of course NASA is concerned about malfunctioning 5G transmitters
leaking into the 23.8 GHz spectrum. Hopefully out-of-band emissions don't
become a problem. It's the FCC's job to ensure that it doesn't, and the lack
of carefulness so far in the process doesn't inspire confidence.

~~~
angry_octet
The fear is based on the already significant interference caused by consumer
devices in other bands. 5G network infrastructure is likely better controlled,
but doing so requires good regulation.

There is some possibility that the 5G systems could actually be used to
measure some atmospheric properties, similar to the way Navstar GPS L1/L2
signals are analyzed, but since that isn't a requirement of the 5G
spec/regulations, it won't be baked in.

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Wiretrip
I have to shout out for windy.com (I am not its developer sadly). It is
probably the best weather site (and app) out there. You can even choose
between weather models.

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gmiller123456
I often wondered the same thing myself, why don't weather providers provide
their own accuracy rates? I started to make a "simple" system for estimating
NOAA accuracy, and immediately ran into trouble determining what accuracy
meant.

If they predict a high to be 86deg, and it's really 85, what does that mean as
far as accuracy goes? If we use the Kelvin scale, even a 10 degree error makes
it seem pretty accurate, though a person's experience in those extremes will
be very different.

But I think the biggest problem is that the simple weather forecasts that we
use on a daily basis, is a poor representation of what weather forecasters
actually do. They're modeling how weather systems form, move, and interact. If
a model predicts storm forming and moving a particular direction, but the 10
day forecast is off by 100 miles causing it to rain a day later, what does
that mean for accuracy? Another model could just use the average weather as
their forecast, and might score pretty high as far as long term accuracy, but
would be pretty useless from a user's perspective.

So, if someone forecasts a high of 86 with a 99% confidence level. What would
that mean. That it'll be 86 somewhere near there, that it'll be close to 86 at
that location that day, or that it'll be 86 at that location within some timer
period? You really can't boil all of those variables down into a single
number.

And then you'll run into issues tracking the confidence of the confidence
levels. Ad infinum.

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ArtWomb
NOAA hosts a Python SDK and REST API for historical data. And I believe they
present at the SciPy conf every year (upcoming in July)

I found this talk by Uber's Danny Yuan super insightful. Forecasting is
probably the subset of ML I am most excited about ;)

Two Effective Algorithms for Time Series Forecasting

[https://www.youtube.com/watch?v=VYpAodcdFfA](https://www.youtube.com/watch?v=VYpAodcdFfA)

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infinity0
It's kinda cool that we _can_ predict in enough time to save lives and
equipment. If our brains or metabolism had been slower, then this might not be
the case, even after we've developed the mathematical theories that we have
now.

