[mikeortman]

Hi, hobbyist here! This is a huge area where government meteorologists and "Big Weather" differ and you can help close that gap!

For context:

The governments of the world provides these big weather companies (weather.com (cough IBM), Accuweather (cough IBM cough), etc) a metric shit ton of their data completely for free (by law) including data transfer. These are things like radar, satellite, ground station data, forecasts, composite models, etc. These companies profit substantially on it, as in billions of dollars. You as citizens also can get this data completely for free as well! MADIS is a system the government is working on to make that data access easier by bringing together many of these systems together and removing the bureaucratic redundancy and abstracting out the aging infrastructure. This is literally terabytes of data per day you can grab with almost no questions asked. That data is then processed privately and resold and repackaged to the end user, and you probably interact with this privatized data the most.

The frustration I have much of the additional "value" these weather data brokers provide is by linking up with each other with data contracts. These private companies have a much much higher detail on the ground than the government by being able to partner with companies that make common internet-connected personal radar stations and reselling that data to each other. The government doesn't have that privilege to buy limitless data. NOAA/NWS, for example, is extremely underfunded so if they had to privilege to buy it they probably couldn't come to an agreement to buy it. As a result, they can't use that data to improve the accuracy of alerts/warnings/forcasts, the same exact tools that the big weather companies make all their money from. It's a shit cycle and totally unfair IMO.

So please contribute if you can!!

Sidebar: I'm a founder of a self-bootstrapped startup to build a better weather data broker that doesn't cost an arm and a leg. If that's something you are passionate about solving, feel free to reach out :)

[open-meteo]

Hi, I am building an Open-Source Weather API aggregating open-data weather models from NOAA, ECMWF, DWD, MeteoFrance, JMA, CMA, CMCC and others. I agree that many weather companies basically redistribute NWS data at a premium. There is a free API service available on https://open-meteo.com and all databases are redistributed via an AWS Open-Data Sponsorship. Feel free to reach out if you need help building your weather data broker startup

[seabass-labrax]

A sincere personal "thank you" from me! I use Breezy Weather[1] on my smartphone, which gets most of its data from your aggregating service, Open-Meteo. It's the perfect combination of accurate, international and open.

[1]: https://f-droid.org/en/packages/org.breezyweather/

[just_testing]

First of all, thank you! What a treasure trove of data.

If I may ask a question, do you have historical air quality data?

[CraigGilmore]

I am working on this kind of solution - please email - see about

[ptero]

Thank you for doing this!

As my own sidebar, I spent many years at a national lab working with distributed sensor networks (primarily ATC and other radar for detecting non-weather stuff :) ). I thought about using ADS-B as input for weather state and forecasts, but never got around to trying it. Now that I am working on my own startup (self-funded and without revenue so far), so this again will likely languish in my todo list. If someone wants to try it, great, and feel free to reach out as I can probably save you some time selecting and interpreting the right ADS-B fields:

We have a lot of aircraft blasting ADS-B reports whenever they fly. Most reports contain (1) accurate 3D position, including altitude and (2) barometric altitude measurements, which gives you (after some minimal work) air pressure. So you have millions freely available pressure reports not just on the ground, but throughout 0-40000 ft altitude band.

You also get measured airspeed and groundspeed, so in addition to pressure you get wind vectors at thousands of points in the air, updating in real time. I suspect this can provide some non-trivial information and I am not aware of anyone actually using it for this purpose.

[counters]

These data are already consumed operationally by the major global weather modeling centers - e.g., check out the AMDAR [1] or ACARS programs. There are commercial agreements which restrict third-party access to these data in real-time, but they are widely disseminate with a 24-48 hour lag in the observational archives that NOAA curates for weather modeling.

These data are a very important input for operational weather forecasting. On a global basis, we've seen how losing these data during the pandemic due to reductions in air travel decreased forecast model skill [2]. Furthermore, ACARS profiles derived from aircraft landing at airports where severe weather is expected are regularly used to complement SPECI weather balloon launches.

[1]: https://community.wmo.int/en/activity-areas/aircraft-based-o... [2]: https://journals.ametsoc.org/view/journals/apme/59/11/JAMC-D...

[madacol]

you referenced "(1)" and "(2)" but didn't provide the actual links

[HumblyTossed]

Don't forget, AccuWeather wanted to make it illegal for you to have access to that data for free from the government.

[widerporst]

Same thing in Germany, with WetterOnline ruminating data from DWD (the German meteorological service) and then suing them when they offered their DWD WarnWetter app for free. Unfortunately, they were successful: https://www.heise.de/news/BGH-Urteil-Staatlicher-Wetterdiens... (Couldn't find an English source, sorry.)

[Wistar]

Alas, there are yet ongoing attempts to break-up and/or privatize the NWS. Project 2025 specifically calls for the break-up of NOAA.

[snowfield]

You can always use yr.no

This is the Norwegian government weather service. It's global and free for everyone. Also has fully open apis

[lukan]

I second this.

It is incredibly fast, no bloat, no ads.

Just not as accurate as a local service as their main focus is - norway.

[_xivi]

> weather.com (cough IBM)

Didn't IBM sell weather.com (and all of the assets) to a private equity? The deal was announced last year and closed in Feb 2024

https://finance.yahoo.com/news/francisco-partners-completes-...

[foobarchu]

Yes, they did. AccuWeather is also privately owned and a major competitor of TWCo. It has never had anything to do with IBM.

[mikeortman]

Yeah, they did... but being blunt, IBM had 8 years to do a lot of damage. Not speaking of the engineers or the tech behind it, I'm talking about escalating the ad revenue and general junk on their website. MOST of the page load time on weather.com and AccuWeather is ad and tracking. It's an ungodly number of requests and will drain a data plan's usage limits surprisingly quickly.

Just opening weather.com will send almost 1000 requests , transfer 10.3MB. Every 30 seconds or so it will make about 300 requests + 2MB of transfer for new ads. It's... insane

[DavidPeiffer]

> These private companies have a much much higher detail on the ground than the government by being able to partner with companies that make common internet-connected personal radar stations and reselling that data to each other.

I haven't heard of personal radar stations, and wasn't hitting anything in a quick web search. Are you able to provide an example of these systems?

[semi-extrinsic]

I'm pretty sure this was a typo, so s/radar/weather/ .

For reference, a weather radar operates in Doppler mode with return signal coming from Rayleigh scattering of raindrops, so it's on the 3cm - 10cm wavelength. You are talking about something like a 5 meter diameter antenna dish that weighs half a tonne, which is on an elevation-azimuth motorized mount, in a 7 meter diameter radome, with peak transmit power of 250 000 W.

Of course you can buy one yourself, if you have the space, electrical power and money for it - ballpark 1.5 mill. USD.

[nl]

My friend built one. Details here: https://www.youtube.com/watch?v=fvxZvObr2hw

[zorm]

Since the Weather Research and Forecasting Innovation Act of 2017, Congress is requiring NOAA to start acquiring data via commercial partnerships.

NOAA has already made some contracts with Spire [1] and Saildrone [2]. I am sure there are more but these are the ones most familiar to me.

Your weather data broker startup sounds very interesting!

[1]: https://spire.com/press-release/spire-global-awarded-nationa... [2]: https://research.noaa.gov/2022/08/03/noaa-and-saildrone-team...

[counters]

The entire slate of commercial acquisitions planned or in progress can be found at [1]. It's pretty anemic; NOAA has spent far less than what folks were hoping they would. I think a major part of this is that the private sector really didn't have very many high-TRL observation systems that could readily be integrated into NOAA's assimilation and forecasting systems. Lots of planned constellations and ideas about things to do in the future, but just not that much stuff that was ready to package-up and deliver to NOAA. The most successful acquisitions for GPS/GNSS-RO and buoy/drone data seems strongly bolstered by the fact that these data were already readily assimilated by existing infrastructure.

The private sector has really embellished its capabilities to the detriment of the CDP and other programs. I think too many industry players saw NOAA's expansion here as a potential slush fund to fully subsidize their R&D, but again the TRL of planned observation systems was too low and so the system didn't really work efficiently. Classic policy failure - would make a fantastic case study or Master's thesis for someone studying weather in an STS program!

[1]: https://www.space.commerce.gov/business-with-noaa/commercial...

[szvsw]

> Sidebar: I'm a founder of a self-bootstrapped startup to build a better weather data broker that doesn't cost an arm and a leg. If that's something you are passionate about solving, feel free to reach out :)

Would love to hear more about this. I’m a researcher and a lot of my work revolves around machine learning applications to building energy modeling, and one of my projects actually revolves around the difference between using TMY vs AMY EPW files in automatic calibration of models. Would be great to chat more. What’s the name of your startup? I can shoot you an email at the official email.

[2Gkashmiri]

I have always wanted to build a cheap ESP based weather station I can give to a friend, have them set up their WiFi and it would transmit data to the central server and I do not want to submit data to AccuWeather or wunderground or someone else.

Is there a Foss server around that I can set up on my own ?

[mikeortman]

https://www.weewx.com

[imoverclocked]

FWIW, purple air is basically this minus wind information.

[tcmart14]

This sounds really cool. Have you looked into see if you can get permission from the guys over at aprs.fi to scrape their data from ham radio weather stations running over APRS? [1]

[0] https://aprs.fi/page/api

[thcipriani]

My rough understanding is CWOP was started by ham nerds and forwards all data to MADIS via FindU[0]

[0]: <http://www.findu.com/>

[8bitsrule]

Thanks for mentioning. When I looked up MADIS, Wiki pointed me here: https://www.weather.gov/ncep/

There, selecting 'Weather Prediction Center' goes to https://www.wpc.ncep.noaa.gov/#page=ovw

There I searched in 'Local forecast' for cities and see most of what 'weather com' delivers, with 3 domains in Noscript instead of the couple-dozen from weather.com

[kmbfjr]

I became so annoyed at the tracking, advertising and poor notifications of many apps, I wrote my own for severe weather alerts.

My hobby will include a C band antenna this fall, and I’m on the hunt for radar data sources in which to create my own mosaics.

[supportengineer]

What is the best option for someone who wants to contribute but doesn’t have a weather station currently or a lot of free time to take on another project?

[jnurmine]

For the data, do you know meteostat.net?

They get input from e.g. NOAA (US), DWD (DE), YR (NO) and so on.

I'm not affiliated, just needed some historical data and (finally!) discovered them.

[just_testing]

If I may use your expertise a bit: I need air quality data for two cities, one of which doesn't have any air quality monitoring stations. Is there anything I can use as a proxy for air pollution, like satellite data? Also, do you know any sources for that data?

Thanks!

P.S.: I'm passionate about air quality, given I have alergies and was an active member of the bicycle activism movement for about 10 years.

[toomuchtodo]

Might find useful info here:

https://www.nasa.gov/missions/tempo/nasa-releases-new-high-q...

https://news.ycombinator.com/item?id=40530798

https://news.ycombinator.com/item?id=40534632

[theyinwhy]

I don't understand why the quality of the specific weather station does not matter. Isn't bad data impacting the overall model quality?

[counters]

> NOAA/NWS, for example, is extremely underfunded so if they had to privilege to buy it they probably couldn't come to an agreement to buy it. As a result, they can't use that data to improve the accuracy of alerts/warnings/forcasts, the same exact tools that the big weather companies make all their money from. It's a shit cycle and totally unfair IMO.

Huh? This is kind of an odd take for a few reasons. For starters, NOAA isn't "extremely underfunded"; with the possible exception of the current budgeting cycle, NOAA generally does pretty well and has strong bipartisan support. It could always use more money, but I wouldn't call it "underfunded.

The reason NOAA doesn't buy more data is because most of the available data has limited value. Personal weather stations have substantial quality issues and add almost no value in areas where we already have high-quality surface observations. We thin out and throw away a ton of surface observations already during the data assimilation process to initialize our forecast models anyways - data from aloft is far more valuable and impactful from a forecast impact perspective.

For what it's worth, few if any companies use proprietary observations to improve their forecasts. It's an open secret that the vast majority of companies out there are just applying proprietary statistical modeling / bias correction on top of publicly available data. Only a handful of companies actually have novel observations, and there's limited evidence it makes a significant difference in the forecast. At best, it can result in the way that those statistical corrections are applied to existing forecasts and ensembles - you can count on one hand the number of companies that actually run a vertically-integrated stack including data assimilation of proprietary observations and end-to-end numerical modeling.

That isn't to say there isn't unique value in the observations. It's just that the industry flagrantly misleads about how they use them.

[amluto]

> We thin out and throw away a ton of surface observations already during the data assimilation process to initialize our forecast models anyways - data from aloft is far more valuable and impactful from a forecast impact perspective.

I regularly notice that the NWS forecasts, even in the very short term, get the surface conditions rather wrong. (This is by comparison to a an inadvertent but, I think, quite accurate surface temperature and humidity measurement that I have.)

I fully believe that the measurements aloft do a great job of predicting the conditions aloft, but I wonder whether the results would be further improved by even a fairly simple model to map the forecast results back to detailed surface conditions. After all, many of consumers of weather forecasts, e.g. people caring about personal comfort, climate control energy predictions and pre-heating/pre-cooling of buildings, etc. care about surface conditions more than they care about conditions aloft.

[zorm]

Very few companies run the vertically-integrated stack because it is prohibitively expensive to do so with current NWP versus what you can sell it for with only marginal forecast improvements. I know several companies have tried this with integrating their own observation sources and ended up with worse performing forecasts. Oops.

I'm very interested to see how the ML modeling revolution changes this. The ability to perform global forecasts on a single GPU should make it cost competitive for more companies. I know several companies are already deriving their own weights for the forecasting component so that they can sell them. Google appears to be working on the next piece of the puzzle too with using ML for the data assimilation step, or skipping that altogether and using observations to go directly to forecasts.

[pinkmuffinere]

Referring to the parent comment, the data which NOAA isn’t able to buy is the government’s data, which is freely provided to non-government organizations. The parent comment doesn’t discuss personal data very much. I think this misunderstanding might be the root cause of your disagreement.

[zer00eyz]

If you see this post, You should go share your story and probably this effort with the Home automation and Home assistant crowd.

As consumers and creators of plenty of weather data you might see a fair bit of traction there!

[mozman]

what’s good weather station hw to get? thinking ultrasonic wind instrument and some type of radar

[FireBeyond]

Doesn't encompass radar (and no home weather station will) but NetAtmo sells one with ultrasonic wind, smart rain gauge, and has a full RESTful API available: https://www.netatmo.com/smart-weather-station

I use this and love it.

[CraigGilmore]

Hi Mike- I am very interested in this and doing some work - please email

[alexpotato]

"The governments of the world provides these big weather companies (weather.com (cough IBM), Accuweather (cough IBM cough), etc) a metric shit ton of their data completely for free (by law) including data transfer. These are things like radar, satellite, ground station data, forecasts, composite models, etc. These companies profit substantially on it, as in billions of dollars"

Michael Lewis' book The Fifth Risk goes IN DEPTH into how Accuweather/Weather.com and the government were interacting (particularly during the Trump administration).

I highly recommend the book in general and for this particular story in particular.

[positr0n]

Do you have a source for sites like weather.com and AccuWeather being part of a billions of dollars industry? That is surprising to me.

[mikeortman]

It's hard to get accurate numbers as many weather sites are privately held. But to give some info:

Weather Company was sold for $2B to IBM in 2015 (and recently sold to private equity for undisclosed amount). Tomorrow.IO has a $1B+ valuation pre-IPO SPAC.

https://www.forbes.com/sites/johnkoetsier/2021/04/08/ibms-we...

[datadrivenangel]

https://en.wikipedia.org/wiki/AccuWeather

[akira2501]

You can't safely fly or sail unless you know and can predict the weather at your destination.

[hejdufufjrj]

Big Weather does provide the data for "free" to the weather widgets on millions of phones and computers.

So they do provide a public service, even if maybe they get too much money from it.

[fallingknife]

Why is this unfair? With these private companies I get access to all this data for free. If the government did it I would have to pay for it out of my taxes. Why do we need the government to provide more accurate forecasts when this is already taken care of by the private sector?

[Workaccount2]

You get that data for "free" or your hand over your browser data - and likely location data, to unknown third party brokers that know more about you than you know about yourself. Weather apps in particular are notorious for selling your location data, since everyone does "show weather for my current location".

It's "free" in the worst sense of the word.

[chiph]

> With these private companies I get access to all this data for free.

These companies are already receiving government data for free. And then enriching it with private weather station data (and ads). So your taxes are already funding some part of it.

As computing power being used for forecasting increases (14.5 petaflops each for both Dogwood and Cactus NOAA supercomputers), having more granular data is going to be useful in improving their models.

https://www.noaa.gov/news-release/noaa-completes-upgrade-to-...

[desert_rue]

It is in the public interest to have both weather and forecasts. Maybe you are like me and look out the window to see the weather for that day, but millions need accurate weather and forecasts. They include farmers, those that run power grids, air traffic controllers, and more.