From the Cliff Mass Weather Blog
Cliff Mass,
Many weather scientists have noted that NOAA’s global weather prediction model, the GFS, is now in fourth place, behind the European Center, the UK Meteorology Office, and the Canadians.
This is pretty depressing considering the U.S. spends more on weather prediction research and development than all those groups combined. This NOAA global model is the foundation of U.S. operational weather prediction efforts; thus, Americans are experiencing inferior weather forecasts as a result.
But it is worse than that.
NOAA global predictions have a severe “drop out” problem in which there are sharp, precipitous declines in forecast skill. Major declines in skill not shared by other major weather prediction centers.
Let me show you.
Below are the skills of various modeling systems from April over the northern hemisphere.
It evaluates the ability of models to get things right in the middle of the troposphere…around 18,000 ft (500 hPa pressure)–for a day 6 forecast. 1 indicated perfect score. Above about .8 the forecast is quite useful. Below ~.65 not so much.
The best forecast is the European Center (red line), while the US model (black line) is generally much less skillful.
Note that sometimes the US model skill drops like a rock to below .7 and on one date to below .6. These are drop outs…and represent severe loss of skill.
Note that the European model almost never does the same.
During the past few days (May 3-4), the U.S. model had another loss of skill (day 5 is shown in this graphic, with red being the US model, blue and black the European Center). Very bad.
Certain atmospheric flow patterns appear to give the US model a hard time. One of them is an omega block, in which a ridge (high) has two troughs (lows) on both sides.
In fact, we had a version of this during the past week (see below)
Important: this dropout problem has been going on for years and has nothing to do with budget cutbacks, fired personnel, or some weather balloons not being launched.
Let us be clear. The U.S. needs a vital, state-of-science NOAA, with weather prediction capabilities that are the best that weather science can provide.
Many of us in the weather community understand what is wrong with NOAA and have concrete ideas on how to fix this unfortunate situation. I have written two published papers on the topic and have served on several national committees that provided strong recommendations.
The current administration wants to fix NOAA and make American weather prediction “great again.” But during the first months of their tenure, it has made serious errors, such as mindlessly firing junior staff.
Will they talk to the meteorological community to develop a science-informed plan that could greatly improve U.S. environmental prediction and do so at a lesser cost than today?
I hope so. It would be a home run for the American people.
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It would be better if weather modeling were left to the private sector. Profit motive, and the need to compete, would keep them honest and focused, or at least more honest and focused than they currently are.
The NOAA personnel that I see comment in public are frequently climate alarmists.
I don’t know if they only hire for climate alarmism compared to meterological forecasting skill, or if I have an observation bias since “climate alarmism” does get them a public platform?
Hiring for something other than forecasting skills would be expected to result in inferior models.
My guess would be that the other forecasting services also have a large number of climate alarmists.
TheWeatherNetwork does.
local weather is required to use NOAA forecast.
I notices this last winter the weather forecast were off by a lot!
Why would the profit motive lead to more accurate forecasts?
Surely it would lead to more profitable forecasts.
Can’t see tourist states or tourist industries sponsoring rain forecasts for Spring Break, regardless of the actual weather.
And while some areas may get focus and accuracy (oil rigs could afford to buy that), the profit motive means that those who cannot pay (like near shore fishing vessels) will have to balance that out. That means increased insurance costs.
In the long term, private companies will not invest in infrastructure improvements, like new weather stations or satellites, as the returns aren’t there.
Market Failure is a myth. The Market is good at what it does – reducing costs for an expected return.
But that does not provide vital public needs. Reducing costs leads to gaps in coverage.
By definition, more accurate forecasts will be more profitable forecasts.
In the private sector, if your product fails, your company goes out of business.
In the government sector, if your product fails, you get an increase in your budget.
Government is always more expensive and lower quality compared to the private sector.
MarkW gets it. A provider could charge more for a better forecast. Lightly regulated markets are incubators of innovation, because there is money to be made through innovation. There may not be a market for six-day forecasts because they can probably never be made accurate enough for human purposes. Current models can’t accurately predict large scale things like hurricane tracks with any degree of accuracy that makes them valuable to anyone looking six days into the future. But if there is no market for them, why is the government spending money to produce them? Busy work for scientists?
Back when I was flying private airplanes I paid for a weather forces subscription. Small boat operators probably do the same, farmers too.
Maybe things like weather satellites should be government supported, but satellites are getting pretty cheap, due to the innovative forces of our lightly (by world standards) markets.
The way to make America great again is to reduce government intervention in the economy as much as possible. That includes doing in the private sector whatever can be done in the private sector.
Read about the futures market in agricultural commodities.
A company that butters the bread instead of focusing on accuracy would soon be ignored and would lose revenue. Competition drives accountability. Only a monopoly can get away with a substandard product.
As we have seen, government and bureaucracy have motives other than being correct.
Exactly! Google DeepMind’s AI model for weather forecasting, GenCast, already surpasses the best weather forecasting models. Close all of the NOAA’s “analysis” endeavors, lay off a bunch of people, many of whom are climate alarmists, and save the taxpayers a lot of wasted money. Focus on weather and climate monitoring and hand the data to groups like GenCast to do the analysis and forecasting.
As long as it’s not WX-Charts. They get it wrong 101% of the time!
If they have a systematic problem, it would seem to be senior staff.
Or any staff at all (see above).
“The current administration wants to fix NOAA and make American weather prediction “great again.” But during the first months of their tenure, it has made serious errors, such as mindlessly firing junior staff. “
Cliff you need to come out and say it, the problem at NOAA is the top management. Lay out the business plan for the current NOAA leadership and clearly tell the new leaders that if they repeat it they will also be fired. There is precious little room for politics in the weather business.
But junior (i.e., younger, less experienced) staff are more recent graduates of the radical progressive university programs. They are generally lower IQ (due to DEI admissions and hiring) and compromised by woke left university influences. Fire them and let them reapply for their jobs, with hiring based on recovered criteria of competence and merit.
Some money should be spent on designing a coordinate system for calculations. Usual latitude-longitude coordinates have a singularity at poles.
I have learned to specify the European model for use in Windy.com. It works far better than other products for my high altitude location in the Rockies. I am pretty sure Don Day weights his forecasts on it heavily also.
Cliff:
Could you supply links to your 2 papers regarding NOAA fixes to improve
its weather forecasting? Thanks!
How much weight is given to anthropomorphic inputs to climate change?
Did you mean “anthropogenic?” If not, then I don’t know what your question means.
Reading the title of the above article, I jumped to the conclusion that the article would be discussing the problem with college dropouts finding jobs coding NASA’s weather prediction models.
Does that deserve a “hit” or “miss” on my part?
And the government can’t even keep thermometers close to reality, even at its own offices: Cliff Mass Weather Blog: High Temperatures, Large Temperature Contrasts, and Crazy Hot Stations