Groundhog Day

[GordMay]

Groundhog Day 2024:

Shubenacadie Sam: NO shadow = Early spring
Lucy the Lobster: SAW shadow = 6 more weeks of winter
Wiarton Willie:
Punxsutawney Phil:

Records kept by the Punxsutawney Groundhog Club show Phil had predicted 108 continued winters, and only 20 early springs, through 2023.
According to the Stormfax Almanac*, Phil has gotten it right only 39% of the time. Canadian groundhogs’ predictions are even worse: based on several decades of data, they are correct only 37 per cent of the time.
According to Encyclopedia Canada, 33 per cent accuracy can occur, just by chance.
As usual, Phil was wrong, last year.

* Stormfax Almanac ➥ https://www.stormfax.com/ghogday.htm

According to folklore, if the groundhog [originally a badger, in Germany] sees its shadow [sunny], on February 2, it will return to its burrow, indicating that there will be six more weeks of winter.
If it does not see its shadow [overcast], then spring is on the way.

No matter what the weather, spring will officially arrive, with the Vernal Equinox, on March 19, 2024, at 11:06 p.m. EST.

[GordMay]

Punxsutawney Phil: NO shadow = Early spring
Wiarton Willie: NO shadow = Early Spring
Fred la marmotte [PQ]: NO shadow = Early Spring


Q: What do you call a Harley Davidson with no tires?
A: A groundhog.

[MicHughV]

When my big toe throbs on Saturday night, February 3, exactly at 8 pm, I can tell we are in for an early spring.
I'm trying to find a way to capitalize on this phenomena, but most people think I'm just weird

[jeanathon]

According to the Stormfax Almanac*, Phil has gotten it right only 39% of the time.



Well still better than your average meteorologist/scientist.
I believe in the rat!

[mbianka]

I just head some place warm for a week each month during the winter months. Makes winter tolerable and gives me something to look forward to no matter what the Groundhog decrees.

[GordMay]

Originally Posted by jeanathon

According to the Stormfax Almanac*, Phil has gotten it right only 39% of the time.
Well still better than your average meteorologist/scientist.
I believe in the rat!

A Meteorologist, working with the National Weather Service, goes to his boss, and says: “Boss, I need a transfer out of Florida. Please send me anywhere, but Florida.”
The boss says: “Well, why’s that Bill? What’s wrong with Florida?”

The meteorologist says: “The weather in Florida just doesn’t agree with me.”


I may be dumb.
But, at least, I get my weather information from meteorologists, and not groundhogs.

[CaptTom]

I don't know why this is bothering me. Normally I join in the fun, mocking meteorologists.

But just like cops and donut shops, the joke is starting to get old.

I can't think of a time in the past month that they've been wrong. They predicted the dangerous flooding we had last month. And the month before. They've predicted the past few snow storms quite well. They predicted the unusually warm days lately, and the cool ones. They've predicted the windy days. The other day when we had a few flakes of light flurries, they had predicted a "4% chance."

There have been a couple of times in the past month that they predicted something, but looking at both the radar and the weather patterns on Windy, I didn't see anything which looked threatening. Then, like magic, the predicted storm developed right where and when they said it would. I always wonder "how did they know?"

Of course there are notable exceptions, and it's fun to laugh about it when they get it wrong. But to be perfectly honest, it doesn't happen very often. More commonly I'm impressed how they got it right. Sorry to be such a spoil-sport.

[jeanathon]

^^^^^ Some areas are harder to accurately forecast than others. I happen to live in an area that is very hard to get right. For sure it has gotten better, but generally can do a better job by putting down the screen and going outside and reading the weather in the real world instead of some model in a distant data center.
Also we suspect our local forecasters have stock in the local grocery stores, and when they need a bump they forecast a apoplectic snow storm to get people to stock up on staples they normally don't eat!

[GordMay]

Our ability to accurately predict the weather is [primarily] limited by three factors:
- the amount of available data;
- the time available to analyze it;
- the complexity of weather events.


Currently:
A seven-day forecast can accurately predict the weather, about 80 percent of the time,
A five-day forecast can accurately predict the weather, approximately 90 percent of the time.
However, a 10-day [or longer] forecast is only right, about half the time.

Meteorologists have come a long way, in predicting weather.
In the early 1920s, it took six weeks, to manually calculate a six-hour forecast, using data, from just two points, in Europe.
Today, satellites, remote sensing data, and supercomputers enable us to predict weather, for various timeframes, from short-term forecasts, to long-term climate projections.
These complex models require millions of data points, including temperature, humidity, pressure, and wind velocity, which are discretized*, to simulate the atmosphere's behaviour.
Forecasts begin with current weather conditions, and the accuracy of this input is critical.

Meteorologists assimilate data from thousands of weather stations worldwide [some weather models use data from over 25,000 weather stations], as well as satellite and remote sensing data, producing a reliable basis for forecasting.
When that data is incomplete, the models must interpolate the missing data between the available data points. As the distance between available observational data points grows, the computer model’s ability to interpolate weakens. The chance of an error occurring during interpolation can go up, depending on the time frame getting analyzed. For example, if the forecast period is longer, the model may have to interpolate more data. This can increase the chance of errors in its predictions.

* Discretization ➥ https://en.wikipedia.org/wiki/Discretization

[jeanathon]

Our local forecasts get nowhere near those numbers. 5 days forecast are around 50%.
Last week checking the forecast (windy and weather/wunderground) at 8 a.m. was told to expect snow starting at 11 a.m. At 11 it was sunny and nice. Checked the forecast and saw the snow was now to start at 2 pm. At roughly 3 or 4 a friend checked and was told it would start at 6 pm. Finally around 4 am it spit some flakes that didn't stick, and we had a nice sunrise followed by a sunny day. Grocery stores were busy as hell though.

[wholybee]

Originally Posted by jeanathon

Our local forecasts get nowhere near those numbers. 5 days forecast are around 50%.
Last week checking the forecast (windy and weather/wunderground) at 8 a.m. was told to expect snow starting at 11 a.m. At 11 it was sunny and nice. Checked the forecast and saw the snow was now to start at 2 pm. At roughly 3 or 4 a friend checked and was told it would start at 6 pm. Finally around 4 am it spit some flakes that didn't stick, and we had a nice sunrise followed by a sunny day. Grocery stores were busy as hell though.

A data point for a single day is hardly evidence of the accuracy of a weather model. One issue that many people seem to have is how to account for "partial credit" when a forecast is close but gets a detail wrong. For example the timing of a front. A storm is predicted, but it shows up a few hours early or late. That isn't completely wrong, and the model shouldn't be graded a 0% in determining it's accuracy.

When giving some credit where it is due if a forecast is mostly correct but off by a few hours or windspeed trends the predicted direction but by a different magnitude, the numbers GordMay are very close to what I figured during my cruising.

[jeanathon]

Originally Posted by wholybee

A data point for a single day is hardly evidence of the accuracy of a weather model. One issue that many people seem to have is how to account for "partial credit" when a forecast is close but gets a detail wrong. For example the timing of a front. A storm is predicted, but it shows up a few hours early or late. That isn't completely wrong, and the model shouldn't be graded a 0% in determining it's accuracy.

When giving some credit where it is due if a forecast is mostly correct but off by a few hours or windspeed trends the predicted direction but by a different magnitude, the numbers GordMay are very close to what I figured during my cruising.

If a significant snow storm is forecast to start in a few hours that closes schools causes people to go a little crazy in the toilet paper aisle, yet the day was actually nice and sunny. And with no more accumulation that night than the normal morning frost. Well that is what I call a swing and a miss. Partial credit? Rat withstanding I'll trust my eyes and nose.

[CaptTom]

The models can also "miss" geographically. The storm tracks a bit to the North or South of where it was predicted. The storm still develops and moves basically (say) West to East as the model predicted, but the people who were expecting the storm didn't get it, while someone else did. Is the model 100% wrong? Well, for some people it was. But I still give it good marks.

Weather is a very complex, chaotic system. So is the universe. In a way, chaos and uncertainty are what make the whole universe what it is. I don't think I'd want to live someplace where everything is 100% predictable. I'd go so far as to say life depends on uncertainty, randomness and chaos, if you want to get down to the level of quantum theory. OK, that's a bit philosophical for a discussion on weather. I'll stop now.

[Bowdrie]

"You don't need a weatherman to know which way the wind blows".
Bob Dylan.

[deblen]

Here in the Maritime Provinces,we like to say -If you don't like the weather,wait 20 minutes
Forecasting has come a long way. I can remember listening to Boston based weather forecast on radio in the '50s with my fisherman grandfather each night.
We live in Bay of Fundy so that was a "long range" forecast I guess
Cheers/Len