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Side note: the “forecaster’s discussion” for your local NWS forecast area is easily the best one you can find. It’s the one all your weather apps and local TV m
by teeray 4y ago
Side note: the “forecaster’s discussion” for your local NWS forecast area is easily the best one you can find. It’s the one all your weather apps and local TV meteorologists crib from. Sure, there’s a bit of meteorological terminology to learn, but they often link off to a glossary (then you can put that term into Wikipedia).
My favorite part of the forecasts is that they tell you unequivocally when they are confident in something and when they are not sure. They are not afraid to say a qualified “we don’t know”. This is is a stark contrast to almost every other forecast falsely projecting complete confidence trying to vie for viewership to attract advertising dollars.
- deleted 4y ago[deleted]
- boredemployee 4y agoSomeone replied, but deleted, asking about forecasting and their values and I'm wondering the same. Is the weather forecast an expected value, like say an average given a forecasted upper and lower bounds?
- jeffbee 4y agoPrecipitation forecasts are systematically and intentionally overstated so people will be prepared.
- hammock 4y agoI once heard that precipitation forecasts represented the amount of land in the area that would see rain, not the probability of rain for the total area. I.e. 50% meant half of the area would get rained on, translating to a 50/50 "chance" for you. Then someone else told me that was bogus, and I suspected as much. It may depend on the source of the forecast
- hansvm 4y agoI'd like a source for temporal correlations. Their models definitely have enough data to differentiate between the following two hypothetical predictions (albeit, predictions are chaotic, but the ability to predict this sort of thing is no worse than the other predictions), but I have no way to parse the result to obtain them: Suppose the hourly forecast has 50% chance of precipitation each hour for two hours. In addition to the points you raise about how to interpret 50% at any moment in time, how are we supposed to know if this means either of the following (or something else): 1. A big storm is passing near a point for those 2 hours, and the only question is whether it passes over it or to the side. I.e., both hours have rain or both don't. 2. A small storm is definitely passing over that point, and the only question is when it will arrive. You either have rain in the first hour or the second but not both or neither.
- guepe 4y ago50% means 50% of models predict rain. They run multiple models (- dozen roughly) and.probability of rain is thr mix of all models.
- maxerickson 4y agoNWS predicts precipitation amounts in addition to probability, by the hour, I don't think they are just reporting what a set of models predict. https://forecast.weather.gov/MapClick.php?lat=40.6924&lon=-89.588&unit=0&lg=english&FcstType=graphical https://forecast.weather.gov/MapClick.php?lat=40.6924&lon=-8... (the narrative forecasts are more compact than the hourly forecast, but it seems like they would at least have overlapping methodology)
- seadan83 4y ago
- dontwearitout 4y agoThey are running ensembles of models to predict the forecast. Chaotic systems are challenging to model, and models aren't perfect, so a collection of models is used (either different initial conditions or different versions of the model, as per https://forecast.weather.gov/glossary.php?word=Ensemble https://forecast.weather.gov/glossary.php?word=Ensemble). This gives you a distribution of predictions, which you can use to produce an average, as well as uncertainty, confidence bands, etc. The quality of these predictions and ensembles is empirically validated using proper scoring rules (https://en.wikipedia.org/wiki/Scoring_rule https://en.wikipedia.org/wiki/Scoring_rule), which is a robust way to measure the quality of a probabilistic forecast. Negative-log-likelihood, a ubiquitous loss function in machine learning, is an example of a proper scoring rule (with a minus in front of it). The science behind forecasting has gotten pretty sophisticated, it's an interesting field.
- hprotagonist 4y agomy favorite feature is the “show diffs” button.
- gsatic 4y agoMore like the whole chimp troupe will agree that chimps can't control the path of a storm. With such problems there is no pressure on the forecaster. But the moment one chimp stands up and says no no I can, and a large enough group is persuaded(even if its false), the game changes. Forcaster will start behaving differently. They aren't machines. They are chimps.
- wildrhythms 4y agoI keep seeing people talking about how X Weather App is better than Y Weather App; I've been using a simple bookmark to my local forecast.weather.gov page for years and it has given me an accurate forecast in plain HTML every time. Plus there's radar and satellite imagery. It's great!
- louky 4y agoSame, and it's got hourly, pretty much anything I can imagine needing.
- zeroping 4y agoI wish the National Weather Service could develop an app.
- daveslash 4y agoI know that this is a little off topic, but speaking of X Weather app.... The habit that I am still trying to break with my kid is that they should not rely on the weather app for temperatures when we go camping. The weather app is an app that reports data from a weather station, it is not a thermometer. If you're camping in a valley or a mountain that's 20 miles away from the nearest weather station, the temperature that your app says is almost certainly wrong. So hard to break that habit of relying on the phone when it's not correct with some of the younger folks.
- r00fus 4y ago
- RichardCA 4y agoIn the days of Gopher and WAIS, they would talk about the different supercomputer models being in agreement or diverging. The NAM would say one thing but the ETA would say something else. If you remember what ETA was, good on you. :) (https://en.wikipedia.org/wiki/ETA10 https://en.wikipedia.org/wiki/ETA10)