[HN Gopher] 300 meters resolution SF Bay Area Forecast
       ___________________________________________________________________
        
       300 meters resolution SF Bay Area Forecast
        
       Author : johmathe
       Score  : 124 points
       Date   : 2022-10-27 15:40 UTC (7 hours ago)
        
 (HTM) web link (sf.atmo.ai)
 (TXT) w3m dump (sf.atmo.ai)
        
       | 2Pacalypse- wrote:
       | This is pretty cool if I do say so myself.
       | 
       | What does the picnic data show?
        
         | johmathe wrote:
         | It's a forecast of the best spots to have a picnic in the bay
         | :) Basically a proxy for the best place and time to be
         | outdoors.
        
       | CoffeeOnWrite wrote:
       | Very cool.
       | 
       | Pedantic but suggest title rename to say "SF Bay Area" or "inner
       | SF Bay Area". SF is just a small portion of the coverage area.
        
         | [deleted]
        
       | 1-6 wrote:
       | TIL Mt Diablo gets cold
        
         | latchkey wrote:
         | It even snows!
         | 
         | https://www.sfgate.com/weather/article/Mount-Diablo-Bay-Area...
        
       | lispisok wrote:
       | If I had to guess they are running the WRF model [1][2]. The AI
       | part is post-processing the model output. With a fair amount of
       | reading the manual anybody can run their own WRF. WRF scales from
       | running on a laptop to supercomputers with 1000s of cores.
       | 
       | [1] https://www.mmm.ucar.edu/models/wrf [2]
       | https://github.com/wrf-model/WRF
        
         | milancurcic wrote:
         | Having worked with WRF for 13 years now, contributed patches to
         | many releases, and built a SaaS business centered on WRF
         | (https://cloudrun.co), I still discover new things about it and
         | run into interesting scientific and engineering challenges.
         | It's not the kind of software that's easily picked up and run
         | by a non-expert. It's a large framework that's more niche, more
         | obscure, and not as well documented as something like, say,
         | Tensorflow. There's still a ton of value to derive from making
         | WRF and similar models more usable by non-experts and without
         | access to supercomputers.
        
         | RosanaAnaDana wrote:
         | I mean up or downsampling is trivial. The question isn't if you
         | can make a raster at any resolution, its if you can make a
         | raster thats accurate and precise at that resolution.
         | 
         | Its not clear to me that this is either.
        
           | johmathe wrote:
           | One of the interesting things the model captures at this
           | resolution is the dynamics of the wind going in the bay
           | through the golden gate. See for instance: https://sf.atmo.ai
           | /wind@37.80911,-122.44543,11.68,36,0,16669...
        
             | zsz wrote:
             | The Global Forecast System (GFS), i.e. the model presently
             | used at NCEP, has a grid resolution of 18 miles (28 km). It
             | is (has been, for years, actually), the second best global
             | forecast system, right behind the European ECMWF (sometimes
             | outperforming it, but on average slightly underperforming
             | it, in terms of accuracy).
             | 
             | I don't know how the ECMWF model works, but even as someone
             | who did not study meteorology (but studied electrical
             | engineering, which forms the theoretical basis of weather
             | forecasting via the Kalman filter), I can say the following
             | (having spent a number of years working at NCEP): 1.
             | Initial conditions/parameters are fundamental in setting up
             | a model run. 2. Forecasts have for a long time relied on
             | ensembles, which are repeat model runs with slightly
             | varying parameters. The idea of ensembles is, if you run
             | enough of them, you will frequently notice one or more
             | convergence(s) that various sets of parameters produce,
             | e.g. where some sets of parameters predict one movement
             | pattern for a hurricane, while others produce a different
             | movement pattern. Historically, such discrepancies were
             | resolved by actual forecasters, who decided based on their
             | knowledge and experience which one was more likely. In
             | addition, they also had meetings every morning between
             | scientists (developing the model) and forecasters (who
             | relied more on general knowledge and experience) and
             | involved occasionally heated discussions between the
             | groups. But I digress. 3. Considering it involves a chaotic
             | system, I cannot say how much value something like deep
             | learning might bring to the table that produces consistent
             | value above and beyond what's already obtained by using
             | ensembles of Kalman predictive filtering. It is however
             | noteworthy to point out that if the grid resolution is
             | 28,000 meters, then it may not make much sense to set the
             | resolution of the model itself substantially lower (like
             | 300 meters), because any resulting data is more likely to
             | be an artifact of the model itself, rather than reflective
             | of real life information. Luckily, this issue has been and
             | is being addressed through the development of rigorous
             | testing standards, which inform of the inherent quality of
             | forecasts produced by a particular model (this is how they
             | can assign an objective rank to e.g. the GFS and the ECMWF,
             | when forecast quality is generally very close and the model
             | producing the most accurate prediction varies between the
             | two). To put it plainly, the degree to which the website
             | mentioned above has any value is based not on its best
             | predictions, but on the overall variance (i.e. how close
             | predicted data comes to actual measurements of the same,
             | which is necessarily retrospective). 4. That said, it's
             | worthwhile to point out that just because it doesn't
             | involve a government agency with something like a thousand
             | employees, hundreds of scientists (in the case of NCEP
             | alone), and very powerful supercomputers, does not
             | necessarily mean it's bunk (even if it frequently does).
             | For example, I do recall Panasonic (IIRC) showing up out of
             | the blue, with its own forecasting system, which was shown
             | to be competitive after requisite, rigorous testing. I
             | don't remember many details and this was years ago--and its
             | disappearance alone is suspect, but it's worth adding for
             | completeness.
        
               | johmathe wrote:
               | While a good set of initial conditions is indeed
               | critical, having a smaller model is helpful for modeling
               | micro climates such as the ones you see in the Bay Area.
               | At this resolution you can have a much more detailed
               | representation of relief and water, which are two of the
               | biggest drivers behind the beautiful dynamics we observe
               | here.
               | 
               | Kalman filtering is only one part of the process, and
               | plays a critical role during the data assimilation part.
               | Classical Kalman filtering is optimal for Gaussian
               | distributed linear dynamical systems, but needs tweaks
               | for non Gaussian distributions and non linear systems.
               | 
               | Classical NWP models for instance will integrate the
               | primitive partial differential equations in time and
               | space and run various parameterizations (which can be in
               | some cases even more expensive than integrating the
               | primitive equations). ECMWF on their end use IFS, which
               | is a spectral method for solving the PDEs.
               | 
               | The whole process of solving these models accurately has
               | definitely been some of the most fascinating science and
               | engineering I've had the pleasure to work with. It's
               | extremely humbling :)
        
         | lbrindze wrote:
         | sure anyone can do it, but it takes a lot of computers to do it
         | at a reasonable refresh rate. HRRR is 3km and available for
         | free. no super computers required by the end user. then you can
         | apply what ever AI/statistical downscaling you want without
         | having to try and run a better/more reliable forecast than the
         | NWS
        
       | cleandreams wrote:
       | Yes, yes, yes. Great. Thanks. Bookmarked!
        
       | Waterluvian wrote:
       | A few thoughts from a geographer (be prepared to shoot me):
       | 
       | - Basically every comment is wowed by this, but nobody questions
       | what the accuracy is. I, too, can Krig interpolated surfaces to
       | any resolution.
       | 
       | - off-nadir view doesn't seem to offer much
       | 
       | - We've been dealing with janky tile loading for like 20 years
       | now. I really hope we'll get a much smoother approach for viewing
       | these tiles as they load. The dissolve transition hides it a bit,
       | but makes the data uncomfortable to view when playing the
       | timeseries.
       | 
       | - I'm deeply curious about the Picnic data layer. Can someone
       | share the ArcGIS/QGIS model for that one? =D
        
         | _Microft wrote:
         | I had been wondering if that was actually something special
         | because I thought I remembered that the German Meteorological
         | Service ("Deutscher Wetterdienst") offered accurate forecasts
         | on a sub-kilometer grid for years already. At least if you are
         | ready to spend money on that because that service is not free,
         | so maybe that's the innovation here.
        
         | wmeredith wrote:
         | Thanks for chiming in. I can make an animation say whatever I
         | want. I am very curious about the accuracy.
         | 
         | Unrelated: The site breaks my back button in Chrome, which is
         | an unforgivable UI sin.
        
           | johmathe wrote:
           | Thanks for the feedback. We will have the back button fixed
           | quickly :)
        
             | thot_experiment wrote:
             | Same thing in firefox, and pleeease have a units switch.
             | Would be infinitely more useful if I could view the site in
             | the units my brain normally works in rather than having to
             | think about the conversion all the time. Very cool site
             | otherwise, also very cool bay area right now.
        
               | johmathe wrote:
               | All fixed up and deployed.
        
         | hadlock wrote:
         | Few thoughts as a sailor in the SF Bay area.
         | 
         | - Accuracy seems at least somewhat correct.That wedge shape you
         | see in the late afternoon sailors call "the wind engine". Local
         | sailing magazine Lattitude 38 has a special PDF that talks
         | about doing a sailing trip around the bay accounting for this
         | local wind phenomenon.
         | 
         | Correct stuff:
         | 
         | - The SF waterfront, out to the edge of the piers is mostly
         | calm which is correct
         | 
         | - Berkely, Oakland, Emeryville getting blasted late afternoon
         | is correct
         | 
         | - Back side of treasure island, immediately to the east is much
         | lower than the west side, particularly near clipper cove
         | 
         | - Vast majority of alameda estuary is dead calm, that's correct
         | for this time of year
         | 
         | - There's a big blast of wind between Daly City and OAK
         | international where there's a gap in the mountains
         | 
         | Weird stuff:
         | 
         | - Most noticable, is the wind is still strong up to and south
         | of the bay bridge. The bay bridge has been described by many as
         | "a wall" when it comes to the wind. There's a drop off but it's
         | not in line with the bay bridge. At all. at least 45 degrees
         | off from true wind speed.
         | 
         | - There's a very windy patch between golden gate coast guard
         | station and belvedere, it's usually really patchy wind here but
         | I guess if the wind direction is just right it'll blow there
         | 
         | - Pointe Bonita (lighthouse on the west side of gg bridge about
         | 2 miles, north coast) they are modeling the gap in the rocks
         | there and you can see it funnel through which is neat
         | 
         | It's a cool visualization though, gives you a great idea of
         | where the wind is, and more importantly where it won't be.
         | There are a bunch of races that start in the bay and head south
         | towards Santa Cruz and Monterey so it's nice to better
         | visualize where the wind just dies off on the coast as it skips
         | over the mountains.
         | 
         | Anyone who wants to see what the wind is like in the bay I
         | recommend reaching out to YRA.org they can put you in touch
         | with a boat who needs crew most likely. There are races 4-5
         | days a week through november all around the bay. It is modeling
         | a distinct drop off of wind speed on the south side of the bay
        
           | UniverseHacker wrote:
           | Also, as a person with experience sailing on the Bay, this
           | model immediately seems unusually accurate. It shows, for
           | example, the Angel Island wind shadow moving around correctly
           | as it does during the day, which I have never seen in another
           | model.
           | 
           | Could anyone with more understanding of meteorology (or OP)
           | please explain what is different about this model vs say the
           | ECMWF model that you can see in apps like Windy, that are
           | supposedly great, but just don't seem to get these features
           | right? Those models are incredibly bad when dealing with the
           | unusual local geographic features on the bay. What resolution
           | are they operating at?
        
           | johmathe wrote:
           | Very valuable feedback - thank you!
        
         | [deleted]
        
         | samvher wrote:
         | This seems to be a thing with weather models more generally.
         | Somewhat relatedly, I've spent quite a bit of time evaluating
         | weather models for use in India and Africa, and while
         | predictions are easy to find, validation results for the
         | predictions are _very_ hard to find. And when you do find them,
         | the results are pretty poor, with many models performing worse
         | than if you would say  "predict temperature on date X to be the
         | average observed temperature on the same date in the past 10
         | years". But people still sell (and buy) these predictions!
         | 
         | Weather predictions seem to be accepted quite uncritically.
         | Perhaps people have a lot of confidence in the smart people
         | that built these predictions (a bit like how AI predictions can
         | sometimes be accepted uncritically).
        
           | Waterluvian wrote:
           | 100% agree. Scientists and engineers all know that you must
           | provide validation results, accuracy/uncertainty
           | calculations, etc. or your data is just a pretty guess. I
           | think weather forecast models are so commoditized and useful
           | for laypersons that we've UX'd all of the complexity
           | (scrutinizing the data) out of the product. The most scrutiny
           | I ever see are people discussing what "Probability of
           | Precipitation" values really mean.
           | 
           | My grad thesis advisor encouraged me to actually get the
           | Environment Canada models and learn how to run them (they're
           | in FORTRAN). I could never make them spit out data consistent
           | with what EC publishes. That's probably on me, but it was a
           | real eye-opener to this whole domain's complexity.
        
           | lbrindze wrote:
           | Given this is in the SF bay there a number of high quality
           | observations that you can use to validate the forecast skill
           | (unlike India and Africa). I have not bothered doing this
           | here since... well that's too much like my day job.
           | 
           | I'm always excited to see new forecast products, generally.
           | If I were to guess (as an above comment did) it looks like
           | they are applying some dynamic downscaling on top of either a
           | custom WRF model (expensive and complicated) or more likely
           | already available weather model data like the HRRR, which
           | still would represent a 10x resolution increase.
           | 
           | I'm more curious what the refresh rate is. Anyone can get a
           | super accurate forecast for the next 3 hours that takes 10
           | hours to run, but at that point it's no longer a forecast by
           | the time the data is available.
           | 
           | I still think that windy has set the standards as far as
           | modern weather visualization goes. Not saying everything has
           | to be particles but other things (like the inclusion of
           | isobars) is really clean and not trivial to execute.
           | 
           | Either way this has definitely piqued my interests and I will
           | be keeping an eye on it, their advisory board looks legit (at
           | least in the meteorology end)
        
             | mturmon wrote:
             | The website claims to be using DL which may mean less of a
             | model-centric approach? The expertise of the people at the
             | top of the organization, on this problem, seems a little
             | thin, TBH. And, no stated validation results at all?
             | Without such details, this is just marketing.
             | 
             | It would be interesting to see how this behaves for longer
             | prediction times and across a range of difficult forcing
             | conditions off the ocean in the BA.
        
               | lbrindze wrote:
               | I agree, this generally left me feeling skeptical. I know
               | of Luca Delle Monache on the advisory team, through
               | colleagues who have researched under him at Scripps and
               | they spoke highly of him. But yes, there is a lot left to
               | the imagination here.
               | 
               | With regards to the sfbay specifically I used to work
               | with a fairly high resolution wind model for the bay
               | (this was a more traditional dynamic based simulation)
               | and it worked pretty well overall, but every time a storm
               | blew through it would crash. This ultimately had to do
               | with the relatively steep terrain in the bay specifically
               | (and the physics configurations we were using in the
               | actual model).
               | 
               | Even if they are using DL they still need initial and
               | boundary conditions. As I said there are a ton of weather
               | stations around so I could imagine a DL type approach
               | that looked at terrain elevation, and recent + historical
               | observations to initialize a forecast, but I still
               | imagine that boundary conditions would have to be
               | provided by nesting this in a larger model somehow. Then
               | again, I'm not a DL expert at all so there are probably
               | some newer stuff in this field that I'm just out of date
               | on.
               | 
               | Its really expensive to run your own dynamic forecast
               | model, at a refresh rate acceptable for an actual
               | forecast, at this resolution. That's why I suspected its
               | taking existing weather models and downscaling them with
               | DL techniques, but I can't really know just by looking.
        
               | mturmon wrote:
               | (For clarity, I was referring to the company leadership
               | proper, not the advisory team.)
        
           | duanem wrote:
           | I've been working with weather models for 10 years and I
           | often get asked "How accurate is X?" or "Which model is more
           | accurate?" Many people think "accuracy" is a single number or
           | a single thing - it is more complex than this and depends on
           | your needs.
           | 
           | This chapter on Numerical Weather Predictions [0] is great,
           | especially the section on "Forecast Quality and Verification"
           | (p777). The eye-opener for me was "Binary/Categorical Event".
           | An example of a binary event is rain, one model could predict
           | rain correctly but a second model might not predict the rain
           | at all. This doesn't mean the second model was completely
           | wrong, it still predicted the rain but it predicted the rain
           | passing further to the south.
           | 
           | [0] https://www.eoas.ubc.ca/books/Practical_Meteorology/mse3/
           | Ch2...
           | 
           | I've also noticed some model are better than other at
           | predicting one phenomena while other models might be better
           | in certain regions. For example, many people report that
           | Canada's GDPS is better at higher latitudes whereas NOAA's
           | GFS is better at equatorial regions.
           | 
           | One final note, just because someone is solving an WRF model
           | without verifying the results, doesn't mean it's wrong. Many
           | numerical techniques and physical models within WRF have been
           | validated analytical and experimental models. But it is also
           | true that someone can naively setup a WRF model that gives
           | bad results.
           | 
           | I use a 900m WRF model that predicts the wind shadow around
           | an island and we use it to find the best beach for a picnic -
           | and it works. But this same model predicts the general
           | pattern of rain but it doesn't get the start and stop time of
           | rain correct.
           | 
           | People get fixated on accuracy as a single thing and use it
           | as a single basis for argument but to take a quote from the
           | chapter [0] above "One of the least useful measures of
           | quality is forecast accuracy" (ref. p777, Forecast Quality
           | and Verification, third paragraph).
        
             | CalChris wrote:
             | > other models might be better in certain regions
             | 
             | The US Navy's COAMPS model is good for littoral regions.
        
             | carabiner wrote:
             | Meteoblue was dramatically more accurate in Chamonix last
             | spring than the GFS.
        
               | duanem wrote:
               | You have to be careful you aren't comparing apples to
               | oranges. You might be looking at the Meteoblue MOS
               | (statistically corrected) predictions which might be
               | based on their regional weather simulation. This regional
               | simulation might be nested in a larger global model,
               | probably from ECMWF. If you compare this ECMWF model to
               | GFS, then you are comparing apples with apples.
               | 
               | I find global models like GFS are great for understanding
               | the large scale weather systems. The regional high-
               | resolution models, which are usually nested in a global
               | model, give better definition of local weather phenomena
               | like wind shadows or cooler temperatures in valleys.
               | 
               | Dues to averaging, weather simulations usually have a
               | bias error in temperature predictions. These errors are
               | corrected using statistics (look up Model-Output-
               | Statistics) but is hyper-local, i.e., you loose the big
               | picture. This is probably what you're looking at with
               | Meteoblue.
        
         | s1artibartfast wrote:
         | >Basically every comment is wowed by this, but nobody questions
         | what the accuracy is
         | 
         | I am very skeptical. Does the San Mateo bridge really block 10
         | knot winds for the entire south bay? Similarly, the land
         | temperatures all seem the same close to sea level.
        
           | hadlock wrote:
           | Tall bridges do weird things to the wind. I can confirm the
           | bay bridge at surface level, there is functionally no wind
           | for about half a mile downwind from it. Just glassy smooth.
        
             | s1artibartfast wrote:
             | Most of the san mateo bridge is quite low, especially the
             | stretch crossing the bay. This is why I was so shocked it
             | had a wind shadow 10+ miles
        
               | hadlock wrote:
               | I'm not seeing much of a wind shadow for that bridge,
               | particularly at 4pm Friday. Maybe they updated the model
               | already. Most of the onshore windflow begins after 11am
               | goes from the cold (high pressure) pacific through the gg
               | bridge, wraps around the east side of angel island and
               | north past Richmond and Vallejo towards the hot (low
               | pressure) central valley. South of SFO silicon valley is
               | surrounded by tall geographic features and there's not
               | much path to hotter (low pressure) zones so it's unusual
               | to see high winds there unless there's a special offshore
               | wind event coming from the south (most often in the
               | winter).
        
       | georgeburdell wrote:
       | Not working on my iphone. Slashdotted?
        
       | FullyFunctional wrote:
       | Sorry, I'm from the present. How does one change it to Celcius?
        
       | mistrial9 wrote:
       | fun - but I am reminded of the excoriation that Windy-dot-com got
       | here on YNews when facts-oriented people started comparing the
       | visualization to more quantitative sources.. snipes aside, no
       | doubts here that they will sell this and be paid for it.
        
       | syntaxing wrote:
       | How much computational power does it take to make something like
       | this?
        
       | blululu wrote:
       | That is impressive. Pretty accurate about the early morning cold
       | spots. Not sure how much of this is just matching historical
       | trends (SF has a pretty consistent climate), but the level of
       | spatial resolution on the data is amazing. Not sure how they did
       | it really.
        
       | modo_ wrote:
       | Running over in Rodeo valley (Marin) there was a very noticeable
       | (and unusual) inversion this morning around 7:30 am. It must have
       | been 5-10 degrees colder on the valley floor compared to up
       | higher -- after ~100ft of elevation gain up out of the valley it
       | warmed up very rapidly.
       | 
       | I don't see that reflected in this map at all fwiw.
       | https://sf.atmo.ai/temperature@37.83200,-122.51075,13.53,20,...
        
         | Workaccount2 wrote:
         | It's likely because services like these use models as data
         | feeds and not live/recorded data.
        
       | anyfoo wrote:
       | Growing up in Germany, before I moved to the Bay Area, I was
       | wondering why weather apps and widgets were so prolific. Sure,
       | knowing the forecast for next weekend was nice, but for anything
       | closer I'd just get out of bed and look out of the window. That
       | would pretty much tell me what weather it is, and it would
       | usually change just slowly over a few days or so.
       | 
       | Then I moved to the Bay Area, and weather does not only change
       | quickly, it may also be vastly, _vastly_ different just a short
       | distance away. Temperature differentials of 10degC or more within
       | just 40 miles are interesting enough that it 's a frequent topic
       | of conversation with friends in Germany.
       | 
       | Everything suddenly made sense. The weather widgets. The hoodies:
       | Easy to put on or off.
        
         | FullyFunctional wrote:
         | Yes. I'm from Denmark, but I check the weather every night
         | before stepping out as I have experience 13 C nights where the
         | previous night was 20 C. And this is not uncommon.
         | 
         | When I first got here I was stunned by how noticeable nicer the
         | weather was when driving from Santa Clara to Palo Alto, and
         | more than once have I forgotten to bring a sweater to SF.
        
           | anyfoo wrote:
           | Yeah. Living in SF and working in the South Bay, it's common
           | in the evening to get into my car sweating, and coming out
           | freezing. I _always_ pack a hoodie.
           | 
           | On the bright side, a hoodie is often all I ever need, all
           | year long.
        
         | anyfoo wrote:
         | Another anecdote: In the South of Germany at least, long
         | stretches of sunny days are often followed by sudden
         | thunderstorms with equally sudden bursts of rain. That "fact"
         | had been so deeply ingrained in me that it was subconscious.
         | You'd have a careful feeling if it was hot for too long,
         | suddenly you might find yourself running for the next awning to
         | escape the torrential rain.
         | 
         | Sunny weather was a bit like building up a sort of pressure,
         | that must release violently.
         | 
         | Took a while to let go of that feeling in California. It
         | basically rains in winter, and does not rain in summer. Like,
         | at all.
         | 
         | (Note that I moved away about a decade ago, climate may have
         | changed in the meantime.)
        
           | dan-robertson wrote:
           | I hadn't even thought of that until I read this. I had
           | thought thunderstorms after hot weather were just a fact of
           | life. I guess in places near German latitudes that get
           | thunderstorms the hot weather is caused by high pressure
           | systems but maybe that isn't really the cause in California.
        
             | barbazoo wrote:
             | Coastal weather is often lacking the conditions that
             | creates thunderstorms. I live near the coast now too and
             | haven't experienced the kind of thunderstorm I know from
             | Germany.
        
               | macNchz wrote:
               | Depends on the coast I guess...NYC, for example, gets
               | some real whopper summer thunderstorms
               | https://www.youtube.com/watch?v=wk3Gz9o9yw4&t=12s
        
           | s0rce wrote:
           | Midwestern USA has similar stretch of hot summer followed by
           | thunderstorms.
        
       | misradeepika wrote:
       | I'm loving the picnic mode!!!!
        
       | modzu wrote:
       | shameless plug of my little rain map that has the opposite
       | approach --
       | 
       | zero interpolation, zero forecasting. just the real data from the
       | radar feed in 10 meter resolution at the current time (plus 3
       | past snapshots at 1 hour intervals):
       | 
       | https://truweather.link
       | 
       | and the app versions:
       | 
       | https://play.google.com/store/apps/details?id=net.conceptual...
       | 
       | https://apps.apple.com/ca/app/truweather/id1537614881
       | 
       | i find it useful because every other weather app is wrong in some
       | way ;) instead, it enables you to form your own mental models
        
       | nathancahill wrote:
       | Wow, this is the future.
        
         | lostlogin wrote:
         | I wish it was.
         | 
         | I see no sign that forecasting has improved at all in my part
         | of the world. Auckland, New Zealand.
        
         | pvarangot wrote:
         | Literally
        
       | bombela wrote:
       | How do you switch to normal (for 97% of humans) units for
       | temperature and wind?
        
         | froidpink wrote:
         | The heaviest users of wind forecasting use knots
        
         | [deleted]
        
         | pklausler wrote:
         | I learned to interpret wind speeds in m/s on a visit to Iceland
         | and found it to be an intuitive unit for hiking and other
         | outdoor purposes. And 1m/s is pretty close to 2 knots so it's
         | easy to convert.
        
       | londons_explore wrote:
       | Weather forecasts are so hard for a user to evaluate... Are you
       | going to check it every day and remember how many days it was
       | right or wrong?
       | 
       |  _Please_ can weather providers just publish a headline statistic
       | of  "Our rain/no rain one day ahead forecast is right 85% of the
       | time. That is better than NOAA (80%), Met Office (72%) and
       | weather.com (65%)."
        
         | carabiner wrote:
         | This is kind of the purpose of the "50% chance of rain" things.
         | The process is called calibration and is usually done with
         | linear regression, and it means that in historical _forecasts_
         | , the _actual_ outcome was rain 50% of the time. Surface precip
         | is notoriously hard to predict, so this is what we 've got
         | right now.
        
           | londons_explore wrote:
           | But they should publish that... And then compare that figure
           | to their competitors... To demonstrate to their users that
           | their service is actually better, not just has a shinier
           | UI...
        
       | s1artibartfast wrote:
       | Very interesting data but infuriating UI.
       | 
       | With so much heat map display, why is there no key? For wind,
       | red/purple are counterintuitively lower speed than orange and
       | yellow?
       | 
       | Also, who do so many applications force oblique views?
        
         | lucasmullens wrote:
         | > Also, who do so many applications force oblique views?
         | 
         | I'm able to adjust it by dragging with two fingers on my
         | trackpad, which I think is the standard behavior for that
         | (albeit hard to discover). But I do agree, it's weird for that
         | to be the default.
         | 
         | There's also probably no key because the colors are mostly
         | transparent, so it would be hard to make a key easy to
         | understand. Labelling the contour lines seems like a reasonable
         | approach imo.
        
           | s1artibartfast wrote:
           | Interesting, I don't get Contour labels on mine, so I have to
           | continually reposition to get a sense of the magnitude
        
       | RosanaAnaDana wrote:
       | so whats the RMSE and how do we know that?
        
       | nicolashahn wrote:
       | I've been wanting this for a long time. Any way I could get it as
       | a live updating widget for my Android home screen?
        
       | dopeboy wrote:
       | Opportune day you picked to share this, given this nasty cold
       | front. Very cool.
        
       | nfriedly wrote:
       | What does "300 meters resolution" mean in this context?
        
         | lispisok wrote:
         | Weather models divide the atmosphere into cells where each cell
         | has it's own forecast. There are several ways to do it but if
         | you imagine the cells as cubes, the north-south and east-west
         | dimensions of the cube is 300m long. 300m is very high
         | resolution for weather models with most running at a few
         | kilometers to a few dozen kilometers.
        
         | johmathe wrote:
         | It means that the underlying weather data is computed and
         | validated at a 300x300 meters resolution. Hope this helps :)
        
           | carabiner wrote:
           | How are you doing validation?
        
       | rnk wrote:
       | Interesting. Their website has a real "Delos" feel, as in the
       | West World corporation. I'd love a narrow cast for my area too.
       | You could sell access to these maybe.
        
       | zestyping wrote:
       | Is there a Celsius mode?
        
       | asdff wrote:
       | This needs to be done for more cities in California, especially
       | Los Angeles with its huge geographic area and all the diverse
       | micro climates contained within. Sometimes the weather changes
       | more than 15 degrees in half as many miles from the coast. It
       | therefore doesn't make sense to e.g. check "weather in LA" when
       | its going to be somewhat wrong most of the time depending on
       | where in LA you happen to be, since the little widget that pops
       | up on google search for "weather in LA" doesn't exactly tell you
       | where in the 500sq miles of LA they are putting the temperature
       | probe.
        
         | sosodev wrote:
         | Same thing in San Diego. I feel like the popular weather
         | services can't make accurate predictions or even tell what is
         | happening most of the time. My iPhone will tell me it's raining
         | when it's sunny outside.
        
         | issa wrote:
         | I feel like you could make a whole movie about the weather in
         | LA. It would change your life. Twice.
        
           | PaulHoule wrote:
           | That's true, but an upstate New Yorker would wonder what the
           | fine resolution forecast looks like for a place that really
           | has weather.
        
           | CalChris wrote:
           | Not weather, sun, sun, sun, sun, sun!
        
       | orangepurple wrote:
       | Looks amazing! However, this model (like all models by default)
       | is not validated and produces garbage unless proven otherwise.
        
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       (page generated 2022-10-27 23:01 UTC)