BECOME A METEOROLOGIST
If your love for weather knows no bounds, you might want to become a meteorologist—but it’s no cakewalk.
The world’s atmosphere is a dynamic, complex machine. To fully understand and predict the weather, you’ll need a thorough grounding in math and physics.
Majoring in meteorology at a university requires a full load of rigorous calculus and advanced physics courses—so many of these courses, in fact, that many students pursuing a life of forecasting wind up double-majoring or taking up minors in the two subjects.
If you’re a hardworking student who’s up for the challenge, it’s well worth the effort.
For those of us who are passionate about the weather but can’t do the math to save our lives, most meteorology programs offer a minor that provides a solid education into meteorology without any of the in-depth science that requires high-level math and physics.
It’s a great option if you’re looking to learn about the weather while pursuing other fields of study.
PREDICT THE FUTURE
All of us have joked about meteorologists flipping a coin to arrive at tomorrow’s weather, but the science of meteorology has advanced to the point where today, our forecasts are extremely accurate.
In fact, we can now predict major weather events days before they happen, when such precision was almost unthinkable just a few decades ago.
THE BASIC TOOLBOX Meteorologists use a wide array of tools to produce their forecasts.
The first step in producing a forecast is to take a look at what’s going on in the atmosphere right now, starting with the upper levels (usually around 30,000 feet) and ending with the weather at the surface.
To begin a forecast, first look at the jet stream or the fast-flowing river of air in the upper atmosphere. The jet stream is the driving factor for most major weather events.
Meteorologists then look at different features in the mid-levels of the atmosphere before arriving at the surface, studying data collected by radar sites (to see precipitation) and the thousands of weather stations scattered around the world.
THE CRYSTAL BALL The next step in the forecast process is to use weather models as guidance to help predict where different weather features will form over the next 10 days or so.
These complicated computer algorithms aren’t the answer—they can often tell an incomplete story—but when good information from weather models is combined with a meteorologist’s knowledge and their experience, the result is an excellent forecast.
Does that mean nobody ever gets a little overexcited and predicts a Snowpocalypse! that fizzles? Of course not. But it happens a lot less often than you might think.
MEET THE WEATHER
The weather is strange in that it is seen as both personal and impersonal. Each weather event can affect our lives in the most profound ways, yet these deeply personal impacts are not at all unique.
The weather plays a formative role in the lives of every person who currently lives, has ever lived, or ever will live, and it will keep doing so until we cease to exist or pack up and move to another planet.
Understanding our powerful and fragile atmosphere is important not only because it affects our lives, but also because it’s just darn cool. So bear with me while I get really nerdy for a bit.
LEARN THE LANGUAGE It seems elementary, but in order to fully understand the weather, we need to understand the terms used to talk about different weather events.
Weather happens at three scales—synoptic, mesoscale, and microscale.
Synoptic-scale meteorology deals with large systems such as hurricanes, nor’easters, and fronts—cold, warm, stationary, and so on—that can have an effect on nations or even entire continents.
Mesoscale meteorology deals with smaller weather events such as squall lines, clusters of thunderstorms, lake-effect snow, and sea breezes.
Microscale meteorology involves weather that occurs on a local basis, such as winds and clouds interacting with individual mountains, cold air draining down into a dip in the terrain, and even dust devils that spin up over a hot parking lot.
KNOW YOUR TERMS One of the most widely employed terms in weather forecasting is “precipitation.” Precipitation involves any liquid or ice that falls from the sky: rain, snow, sleet, freezing rain, hail, and graupel.
We will get into all of those precipitation processes in due time. Along those lines, we will talk about “severe weather” quite frequently, especially when it comes to springtime.
Events such as blizzards and flash floods are certainly good examples of severe weather, but we will use the term to refer to severe thunderstorms or those thunderstorms that produce damaging winds, large hail, or tornadoes.
GET A GOOD MODEL
A weather model is a complex computer algorithm that scientists use to help predict the weather.
While they’re not the sole tools meteorologists use to create forecasts, models are an integral part of the process.
Without weather models, our ability to predict the weather would revert back to the methods used in the mid-twentieth century—making it hard to predict the weather tomorrow, let alone five days in advance.
These advanced models need to know what the weather is doing right now in order to predict what it will do in the future.
The computers need to be fed current weather conditions gathered by surface weather stations, weather balloons (as well as some high-flying aircraft) and satellites, along with weather radar.
These models are then able to plug all of those current observations into the various algorithms, and then, using climatology (past weather) for guidance, they can help forecasters issue reliable predictions.
There are dozens of weather models available to meteorologists on the Internet.
Some of them are provided for free, such as the ones run by the United States government, while others are stuck behind a hefty paywall, such as the model run by the European Centre for Medium-Range Weather Forecasts, often called the ECMWF or “Euro” for short.
Each model has its strengths and weaknesses. The United States’ Global Forecast System (GFS) weather model is run on a global scale; it’s great at handling large-scale features that cover entire countries, but it doesn’t do a very good job with small-scale features that only span a couple of counties.