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It’s not an “officially” kept record, but …
West Seneca (about 7 miles southeast of downtown Buffalo) … with 7” of this falling in just one 30 minute period between 3:30 p.m.-4:00 p.m. on December 2nd according to local storm spotters. If true, this would be one of the, if not the, most intense point snowfall on record anywhere in the world. [emphasis added]
My grandmother lived in West Seneca, but I can’t remember stopping in that town in the last 25 years. I grew up just below the “m” in Williamsville in the outer ring of this diagram of that storm.
Here’s what it looks like when the snow starts to come into Buffalo:
Shame on The Wall Street Journal. Justin Lahart’s second page piece features three time series graphs comparing this recovery to earlier ones.
But it cherry picks the comparison set.
I am no great bellyacher about how weak this expansion has been: we don’t have a huge sample of expansions, and amongst the small sample we have, this one looks OK. Not great mind you, but passable.
Here’s the charts in question:
Note that they just happen to miss the recent recovery that might make this one look bad: the post-1982 one.
It’s pretty easy to say this recovery looks normal when you drop out the one that everyone knows makes this one look abnormally weak.
Read the whole thing. It’s in the June 13 issue on page A2, and is entitled “What It Would Take to Do a Double Dip”.
What’s up with folks in Minnesota and Colorado? They need to stay in more.
I’ve lived in four places extensively: Buffalo (3rd group), Tuscaloosa (4th), Salt Lake City (1st), New Orleans (3rd), and Cedar City (2nd). These rankings seem about right to me.
Oh … and I can’t count either.
Via Bookofjoe.
Start today in Kansas City … and drive over 18K miles over the next 35 days and you can see a baseball game in every major league ballpark. With no doubleheaders!
How does one figure this out? Linear programming — the old standard of management science.
This is an example of a network programming problem, as in Chapter 12 of the Powell and Baker MBA
The decisions form an array: 30 ballparks against some number of days (larger than the likely minimum number).
The objective is probably to minimize the number of days (although it could be driving miles too).
The constraints are that 1) each park is visited one time, 2) there is a game at the park that day, 3) on each day there is at most one game to be seen, 4) drive time between games must be possible in 12 hour stints with 8 hours off in between (there’s no mention of the highway speed assumed).
The article from the June 3 issue of The Wall Street Journal says:
… Blatt plugged the schedule for each team into his model, while setting one key parameter: For every 12 hours of estimated driving between ballparks, the system must allow for eight hours of rest, ensuring that the road trip is, at least in theory, humanly possible.
If you think about it, there are probably a lot of ways to get to 30 parks in 30 days. But most of those would be pointless ones, involving trips from NYC to LA to Philly to Seattle on consecutive days, and so on.
That “key parameter” is what makes the trip “humanly possible” by car, because it gives you 45 hours to do the longest trip (1,530 miles) from Houston to LA, 39 hours to do the 1,330 from Seattle to Colorado, and 27 hours to do the 1,047 miles from Colorado to Milwaukee — and you only get one break on that last one. After that, the rest look ease.
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