Since my first day as an undergraduate meteorology student at Penn State, I was exposed to weather forecasting through the Penn State Campus Weather Service club. There are two branches of the club: the communications branch and the forecasting branch. The communications branch provides daily radio broadcasts for clients and video forecasts that are uploaded online. The forecasting branch prepares five day forecasts for various regions across Pennsylvania, which are also uploaded online for the public to access. Included in the five day forecasts are high and low temperatures, precipitation, a brief description of the forecasted weather conditions, and a forecast discussion. I spent most of my time as a member of the forecasting branch. I learned the basics of weather forecasting from upperclassmen who had been a part of the club for a few years. By my junior year, I became a shift manager. As a shift manager, I supervised students to make sure all of the forecasting zones were covered. I also helped teach new members the basics of forecasting, as the upperclassmen did when I was a new member.
My weather forecasting experience also stems from my participation in WxChallenge, the national collegiate weather forecasting competition, as a member of the Penn State team during my junior year. The Penn State team has won the competition the past four years. The competition consists of making forecasts four days a week for ten cities across the United States. Each forecast includes four variables: high and low temperatures, maximum sustained wind speed, and the amount of precipitation to the nearest inch. In the 2014-2015 forecasting season, I placed in the top 50 forecasters in the competition out of a total of 1900 forecasters.
In the summer of 2015, I transitioned to working as an Air Quality Forecasting Intern in the Penn State Air Quality Forecasting Office, learning about operational ozone and PM2.5 forecasting. I had talked to a few of my professors about how to incorporate chemistry into my meteorology degree, and they guided me toward a focus on air quality. I took a few classes that concentrated on air quality and environmental policy, and I found them very interesting. I knew that focusing in air quality was the path that I wanted to take. I found the air forecasting internship through a classmate, fellow intern Lexie Herdt. This internship was the first experience I had dealing with air quality outside of a classroom setting. I found that air quality forecasting is similar to weather forecasting, but there are small differences that distinguish them.
One key difference I noticed was not having to decide on an exact value for temperature or the amount of expected precipitation. As a weather forecaster, most of my time was spent trying to decide on a single value to forecast for temperature or precipitation. For example, to make a perfect forecast in WxChallenge, every variable had to be narrowed down to a single value. If the temperature was off by a few degrees Fahrenheit or the amount of precipitation was off by a few hundredths of an inch, then error points were assigned to the forecast. The most accurate forecasts were given the fewest error points. So getting the forecast exactly right was essential to doing well in the competition. When transitioning to air quality forecasting, I found that narrowing down the temperature or precipitation forecast to a single value is not as essential as it is in weather forecasting. Knowing a range of expected temperatures (e.g., upper 80s °F to low 90s °F) or intensity of rainfall (e.g., light or heavy) is sufficient to make an accurate air quality forecast. For example, if a storm system moving through an area was expected to produce widespread rainfall for an entire day, then I would expect that the atmosphere would be cleaned out and that clouds would block ozone formation. Knowing the total amount of rainfall, whether it’s only 1 inch or 5 inches, is not essential. Dealing with a temperature forecast in a small area can be difficult as it can vary greatly in a very small distance. Determining a range of temperatures works well to make up for this issue when making an air quality forecast.
Having the public affect the air quality forecast is another difference I found. Typically, the public is impacted by the weather forecast. For example, if there is going to be a heat wave or a crippling snowstorm, then the public will have to adjust their plans accordingly, whether it involves travel or outdoor activities. With air quality forecasting, the public can impact the forecast through, for example, holiday travel and fireworks. Typically, the highest volume of traffic and vehicle emissions occur during the work week, Monday through Friday (and sometimes on Saturday, too). As a result, the highest ozone levels are seen during the work week, all things being equal. On average, ozone levels are lower on the weekends due to the lower vehicle emissions. However, on holiday weekends, such as Labor Day or Memorial Day, more people are likely to travel and vehicle emissions are higher than on a corresponding average weekend day. The higher concentrations of pollutant precursors from increased holiday travel emissions can lead to higher ozone levels than what is typically expected. We saw this in Philadelphia this past Independence Day holiday weekend, when ozone exceeded the NAAQS by 1 ppb at one monitor on Sunday, July 5; this exceedance was almost certainly attributable to the higher holiday emissions.
Fireworks celebrations can impact an air quality forecast by causing increased concentrations of particles. When a firework explodes, fine particles are expelled into the air from the smoke associated with the firework. During a typical fireworks show there are hundreds of explosions. This can cause a buildup of particles, especially if the wind is very calm and the smoke plume is stagnant. If the wind is light, it can blow the smoke plume away and cause a buildup of particle concentrations downwind. The impact of fireworks tends to be more localized rather than region wide, but they still have to be taken into account as part of the air quality forecast.
In addition to learning a new skill with air quality forecasting, I improved my weather forecasting skills considerably. Before my internship, I would only have to look at all of the weather observations and models a few days a week, especially on a synoptic scale. During my internship, I looked at observations and model guidance every day. My communications skills improved as well from writing the technical 5-day medium range air quality forecast discussion and the short 3-day air quality discussion for the public. Despite there being small differences, my improvement shows that weather forecasting and air quality forecasting have a strong connection.
