Hello! My name is Ariel, and I have to ask something regarding my future in college. I’ve been aspiring to be a meteorologist for as long as i can remember. I would love to persue a career in this field! I am currently a high school Junior, and in the next couple of months I will be applying to colleges that offer Atmospheric Sciences/Meteorology as a B.S. Major. Those colleges are all SUNY colleges (Oswego, Brockport, Oneonta, and Albany). Assuming that I get into one of these 4 colleges (Oswego is my top choice), I would like to know what i can do to prepare myself for the courses I will be taking in only less than a year and a half. I have been doing resarch on the courses I will be taking (Mesometeorology, Synoptic Meteorology, Climatology, etc), and I would like to know, what exactly can I do in order to be as well prepared and qualified as possible to take these courses? I would say personally, I have a lot of knowledge on weather, but obviously since these are courses for Majors, they might tend to be more speciifc and difficult. If anyone on this website is a Meteorology major or anything similar to that sort, I would highly appreciate advice! Thank you!
Expert Memberposted: 1493036195
It sounds like you’re already quite ambitious, and share the passion of all things weather with me! Those are great schools to choose from. There are also a number of great websites and tools you can check out online. For example:
The storm prediction center, (really any of NOAA sites), a computer model site such as http://mag.ncep.noaa.gov/model-guidance-model-area.php
and of course, weather.com!
Some colleges offer great sites as well:
What you plan to do with your meteorology degree also matters. For example, if you want to be in the field of broadcasting, public speech skills will also come in handy. Learning to be clear, yet concise, is good no matter where you end up!
Geography is also a must! Not just knowing the states, but also climate regions, topographic features, river basins, etc. This will help with forecasting, as well as communicating important information.
I highly recommend an internship while you’re in college. This is what I did, and was the experience I needed to land my 1st job. You can also be a weather spotter with the National Weather Service. Look up when and where they have sky warn training.
Hope this helps! Best of luck to you Ariel!
I am taking a metrology right now at a community college. But I agree with Kelly those links are really good. We’ve used the NOAA sites a lot in my course. I even go on it in my free time!
try this although you can kinda just look it up on google. i’m going to do meteorology too.
A good place to start is by paying very close attention to the high school physics classes you will be taking. Ignorant people often misuse common physical terms…you may hear someone describe force but call it momentum, or describe energy and call it power, or some weird combination of the above. Getting clear in your own head, what
- Energy, and
actually mean, will be an enormous help in making sense of those intro-level Meteorology classes, and will put you in a good place, when your Junior year rolls around and you start fooling around with actual numerical forecasting models and learning under what conditions they develop systematic forecast errors and why. Those models are based on a branch of physics known as Fluid Mechanics. I studied chemical engineering many years ago and we had Meteorology students in my Fluid Mechanics classes…the principles governing the flow of a gas that has clouds of condensing liquid in it and flying-around solid particles, are the same…no matter whether the gas is carbon monoxide and the solids are lumps of soot that came out of an oil fire and the condensing liquid is Dimethylnaphthalene and the flying-around is happening inside a pipe in some factory…or whether the gas is air, the liquid droplets are water fog, and the solids are bits of sand that got lifted in a dry thunderstorm, all flying around outside. Bottom line: A lot of science begins with an accidental discovery, a principle gets understood, and then other scientists find ways to apply the principle, toward understanding a thing that once seemed totally unrelated.
What helped me, was that 2 of my very best instructors were sticklers for Dimensional Analysis. When they wrote an equation on the board (we used chalk boards back in those school days), the equation would contain Numbers and Measurement Units. If the left side of the equation and the right side of the equation, had different measurement units in it, either someone skipped a step and forgot to show how one measurement implied another, or else the equation was meaningless. Learning to check the equations to make sure they make sense, sharpens our understanding of the subject matter.
Prof John Robison, who taught at Edinburgh in the 1700’s, pioneered the concept of Successive Approximation. An equation didn’t have to be perfect, he taught. It just had to get closer to the correct answer, than guessing. A better equation just had to get closer to the correct answer, than the previous equation did. Interesting guy to read about.
Meteorologists make heavy use of Robison’s concept, with forecast models. We can’t possibly know every tiny influence that makes small currents of air move in various directions, (think “butterfly wings” and “falling acorns”) so we ignore 99% of them and measure the ones that will have a huge and immediate effect. Using fluid mechanics principles and a lot of computerized calculations, we simulate how air, water, and land would interact to cause weather, if the 1% were the only influences that mattered. And over a period of several days or weeks, the prediction reaches what’s called a Chaos Horizon, at which the forecast is equally likely to be wrong as correct, because the 99% of small influences that we kept ignoring, finally added up to a significant error between what was predicted and what’s actually happening. Chemical engineers cheat on this part: If there’s a chaos horizon, we redesign the process equipment to remove some of the causes of error, and keep going until things in our simulation converge without any buildup off chaos…although even we like to accumulate big data and find neat tricks to squeeze better product quality and reduced energy use, out of the equipment we’re running. A classmate figured out a quality hack, that happened every time a particular distilling column got heated by the sun on one side…the equipment now is programmed to check the weather! Meteorologists don’t have the luxury of filing the rough edges off of mountain ranges, hence, realistic models have chaos horizons. (The GFS model run by the National Weather Service, only runs out to 192 hours in advance of the present set of observed weather. It’s never accurate at 193 hours. But it’s quite useful at 72 or 96 hours out. What makes it more useful to forecaster is that several competing models are also available, for comparison.)
Your job, as a forecaster, is to understand why the various models tend to make certain kinds of errors, and construct a forecast that relies on the model that works the best, under the weather conditions that are developing, and that best serves the needs of your customer. (Customers? For a Forecast? Here’s an Example. An airline flying over-the-pole passengers and cargo between Detroit and Shanghai, needs to know if a major winter storm will close the destination airport, to cancel the flight when that may happen, as there’s no easy place to refuel in the Arctic Ocean, and the people and cargo will have to fly later. But a ski resort wants details about how much snow will fall in the storm, so it can buy advertising. Two information users, with two distinctly different needs, both related to the same storm. With your training, you can serve them both, with what they really need to know!) So, it will help to have a good handle on these basic physics concepts, so the nerds with PhD’s who write and update the models aren’t talking completely over your head, when you attend a refresher course on how to use the latest version of a forecast model.
One more thing: In the old days, being a stickler for details got people labeled as geeks. When I was a kid, geeks didn’t have role models to look up to.
Thankfully, you do.
Embrace your inner geek.