Climate vs. Weather

What’s in a number? Well, actually, a lot can be stated or summarized in a single number! Sometimes, way too much can be stated in a single summary so that you lose the details of how you arrived at that point. That’s how climatology works. Too many times, we say “the average high” or the “average low” for a particular day is this or that. For example, today’s averages at the Birmingham International Airport are 56 for a high temperature, 35 for a low temperature, and according to the books, we should see, on average 0.14” today. The actual weather that we experience will most likely be significantly different than the averages.

Sometimes we call those average highs, lows, and rainfall amounts the climatology data for a certain city on a certain day. It’s useful because it gives us a meter stick to measure extremes by, but that’s about it. Climate data is measured over 30 years, so if you took every single high temperature and low temperature for today and averaged them together, December 14, you would come up with 56 and 35. All rainfall measured is averaged too, and it comes to 0.14.” Yesterday’s weather compared to that meter stick was “below normal” with a high of 52, low of 28, and no rain at all. It was close enough to the average, though, to say it was “a typical December day,” and it reinforces the flawed idea that all forecasts should trend toward climatology.

As meteorologists, sometimes we (or at least I) have a tendency to be conservative with a forecast because I focus too much on the meter stick and not on the entire picture. That’s a dangerous place to live because there are going to be extreme events that get “evened out” when everything gets averaged up. That record high of 77 set back in 1971 and the record low of 14 in 1917 don’t really stand out in the 56 and 35, but they are there! The big Blizzard of ’93 doesn’t show up well in the averages for mid-March, but it is in there. Hurricane Ivan’s rain doesn’t show up well in the September rain averages either! The point is simply this, just because the books say that Birmingham’s average high for today is 56 does not mean we will always be close to it.

If we always stay with climatology and averages, then there is no way we will ever get an idea that something extreme could happen. The atmosphere is a complex ocean of air with many currents moving air around in all directions. Forecast models do an o.k. job of guiding us toward a forecast down the road, but those models are very near-sighted. After 72 hours, they really start moving toward climatology and away from extreme ideas. You can bet your bottom dollar that no forecast model seven days in advance forecasted a low of 2 above zero in Birmingham on the morning of March 14, 1993 after 13 inches of snow had fallen in the two days prior. Climate data is great. We need a good climatology of an area, but to get the full picture of how the weather really is for a region, state, or city, sometimes you have to go beyond just a simple number.
Posted by Daniel from Cullman  
on December 14, 2005, 8:37 am
That was awesome Jason!

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Posted by  
on December 14, 2005, 8:44 am
Thanks Jason!! Glad to see you here!!! You have a special way of explaining things, making it really simple, and I really appreciate that!!

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Posted by  
on December 14, 2005, 8:52 am
thank you for the information. I have been following the blog farily regularly since hurricane season. I am learning from you guys, but still stuggling on many points. Is there a good source for learning more about these models and graphs and charts? I can hold my own on the hurricane stuff ( too many years to admit watching them come towards my family in Gulf shores!) but all these others are Greek. how about where to begin to learn what the letters for the models stand for. Any suggestions for resources, Web or paper.
thanks guys. And my 2 cents. Thanks to the folks at ABC 33/40 for your strom coverage. The public often takes for granted that you will be there, forgetting you leave family and home to keep us infomred and safe. Thank you and your families. God bless each of you.

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Posted by  
on December 14, 2005, 9:07 am
A little sleet mixed in with rain on Forrest Ave in Gadsden..... Dance, Stephanie Dance!!!!!!!!!! :)

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Posted by  
on December 14, 2005, 9:15 am
Well done Jason keep up the good work and Stephanie you need to dance today because I am tired. Danced all day yesterday and look what happens we get rain so my dance is no good.

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Posted by rusty Pitts  
on December 14, 2005, 9:34 am
Laura , the best way to learn , is to fake it.....HAHAHA just kidding.... There are great resources that you can use...You see a lot of the web sites that are posted by myself as well as Josh, becasue we cant make it all fancy like the abc team... But you can take any of those links and then go to the home page for that specific site, and then go to resources... You can also just do a web search for weather model information ..I will post some sites later today that you can use....

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Posted by Anna  
on December 14, 2005, 9:39 am
As always...a top notch team keeping us informed...we can choose to look at things one way or the other, but someone has to put the information out there!!

Anna

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Posted by Paul  
on December 14, 2005, 10:04 am
Excellent post!The last paragraph particularly puts things in perspective.

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Posted by  
on December 14, 2005, 10:07 am
Laura, the best thing to do is focus on a few maps that can be useful to ANYONE, meteorologist or not.

These include the following: (all can be accessed by clicking the link for "model data" on the ABC3340 weather page)


1. MOS (model output statistics)
Some will tell you these are useless, but that is not true. They can be wrong, of course, sometimes very wrong. Nevertheless its a good "first glance" at what is generally expected. They are very much consensus-average based but guess what? Those averages have formed b/c that's what USUALLY happens. They will not handle the specifics of a strange storm...but can at least give you a rough idea of highs/lows and if any precip is expected. Take this output with a WHOLE shaker of salt.

2. GFS/NGM 4 panel charts. These give you a simple set of images to show 1) amount of precip, 2) type of precip (by looking at the 850mb freezing line, etc) VERY crucial chart to look at, especially during winter.

Start with those two... Then move on to others. It will be confusing at first, but on the bottom of the model info page you will find links to where you can learn more info about how to interpret what you see. don't get overwhelmed. Just try to look for a few key factors that can tell you alot about what the computers are "thinking".

**And DON'T FORGET TO READ THE MODEL DIAGNOSTIC INFO***. This will let you know which, (if any) models initialized poorly (i.e. got the CURRENT weather situation wrong...so future forecasts already doomed to failure)

Good luck and have fun!!

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Posted by  
on December 14, 2005, 11:04 am
Good to hear from you Jason!

No rain in Oxford yet... pretty windy, but not a drop of rain where I'm at.

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Posted by strmspotterchck  
on December 14, 2005, 11:11 am
I was discussing this very thing with someone, especially the fact that no matter how deep into winter we get, it always warms up to rain or we average the 50's....:(

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Posted by Jason  
on December 14, 2005, 12:11 pm
Here are some #'s for anybody arguing for people to go by averages or normal values. These #'s may be off by one or two but it really makes no difference.
From Dec 1, 2004- February 28, 2005 (90) days, there were 11 days that had 50's for highs and 30's for lows. Dec= 4 days Jan= 2 days Feb= 5 days. Thats about 12%

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Posted by  
on December 14, 2005, 4:07 pm
thanks folks. I'll keep pushing through. growing new brain cells keeps you young right?

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Posted by Mark  
on December 14, 2005, 5:47 pm
In conjunction with the average, one can find the simple standard deviation for a better idea of the predictability of the climate.

To compute simple standard deviation, subtract the average temperature from each annual high temperature for the day of interest for the location and then square the result for that day. Do this for every reliable high temperature for the day and then add all those squared numbers together. Take that sum and divide it by the number of days for which you calculated the square of the temperature difference. Then take the square root of that and you have the standard deviation, which is basically the average difference between the measured temperatures and the average temperature. You may also do the same computation for the low temperatures.

If the standard deviation is large, then the climate swings from extreme to extreme over the years. If the standard deviation is low, then the climate is more predictable. This still does not count out the occasional wild anomoly.

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