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Forecasts in my area in Vermont used to be quite accurate, even a week out. Lately the range of accuracy seems to be about 1-3 days. There are several possible causes. NOAA is getting much less sensor data from commercial aircraft because planes are not flying as often. Weather has also become more unpredictable, the current polar vortex intrusion into the USA is a great example; I've been reading the forecast discussions for my area and the forecasters are less certain about my area lately because it is now on the edge of systems being pushed around by the vortex. A slight change in the wind now can make a difference between 0.4" of snow and 5" of snow here. I could imagine this affecting models also, which tend to rely on past behavior and now have to contend with a not unprecedented but still fairly radically different situation. I've also noticed over the years that different sources of weather info are more or less pessimistic. Weather radios always had very accurate forecasts that were a little pessimistic and included some discussion of the possible variances and were used by many planners, police, fire depts, transportation companies, pilots, etc. I haven't listened much to weather radio in recent years so I don't know if that has changed. However the forecasts on the NOAA web site have become progressively more cheerful over the last 10 years or so, predicting sunny skies more often, and only changing to reflect a coming storm as it gets closer. They did change the way the "percent chance" numbers work some years ago (7+ years ago?) so they tend to be more accurate (40% chance of snow used to be an almost certainty here, now 50% is close to 50%). Forecasts, at least the ones indicated by icons and a line or two of text, have become much more optimistic only shifting to become more accurate 1-3 days out from the actual approaching events. If you read the forecast discussion you'll get a more accurate picture of what to expect, but it is pretty technical and not easily understood by your average reader without spending some time getting to know what all the acronyms and special phrases mean (also there is a tendency to use names of geological features as boundaries for weather phenomena, and not many people know these names for the whole surrounding area any more, e.g., river valleys, mountain ranges, local names for areas around larger cities, etc.) I get the feeling (no hard evidence) that the happier forecasts might have been done for political reasons; a cheery forecast makes for a happier nation. It leaves people less prepared for severe weather, but they do still have several days warning and improves the nations mental health (not an insignificant concern). So my guess is that lately the pandemic has reduced the amount of data they have to work with (besides the aircraft data maybe companies that ran weather stations have gone out of business or states have cut back on maintaining weather stations to save money?) and that is to blame for any recent destabilizations of predictions. Possibly the polar vortex is also responsible for uncertainty in forecasts in recent months. The cheerier forecasts could be just a calculation on the part of the service itself; it's tough to be the bringer of bad news and people naturally start to hate you for it (try doing QA on software and watch people cringe as you walk towards them with news of the latest bug in their code) so maybe they tried a more positive outlook to try to get people to treat them less like ogre's. Could be something presidents ordered also, to make people happier so they'll get re-elected. Or maybe there are technical reasons like now they rely to greater degree on models whereas before they relied more on people. Possibly whoever wrote the models built in their own biases and decided all on their own that the weather should be cheerier! Maybe forecasts now use machine learning and the training data's accuracy has faded with time or had biases to begin with. Some web research would probably turn up some history of weather models in the USA. There are probably a lot of scientific papers about the models as well. Note also that the NOAA web site typically provides some maps which show model output in more detail and which you can scroll forward in time (I wish it was easier to see past predictions also) to see how regions are expected to change over time in air pressure, temperature, precipitation, and more. There are regional differences in forecasting too, with forecasters tending to be located near major cities where forecasts are tuned for the local area. The people behind those forecasts do change over time, and likely some aspects of the forecasts also change with them. One thing you can do to improve forecasts in your area is to set up a weather station and send the data to NOAA. That also lets you make your own assessments and get to know the seasonal changes in the behavior of your local weather. There's been some talk of microclimate forecasts; I think that would require a big increase in the number of sensors scattered around the USA, e.g., it might be possible if all the outdoor Internet of Things sensors reported weather related data to NOAA (and they had some sense of what the accuracy of different kinds of sensors was). Maybe cars could become part of the weather sensing system. |