Improvements in Weather Detection in Aviation
Anfernee Emerenciana
Florida Institute of Technology

Abstract
When it comes to flying, planning is everything; one of the biggest things that pilots need to take in to account is namely the weather. There are two key components when it comes to weather planning: forecasting and detection. The FAA and other meteorological organizations are continuously coming up with improvements and new ways to give pilots the necessary weather information needed in order successfully and safely do the flight. This paper will discuss how weather detection and forecasting have improved over the years, what the current developments are, and also what is still left to be done in order to ensure proper planning and overall safety for the flight

The Federal Aviation Administration is a federal branch that focuses on the overall safety and regulations in regards to aviation in the United States. A pilot is required to get a weather briefing before each flight. These weather briefings are offered by the FAA in conjunction with Lockheed Martin. The weather briefings provide weather information products that give important information in regards to winds, cloud ceilings, icing hazards and turbulence. According to Gloria J Kulesa (2004), the weather phenomena’s that have the greatest impacts are: in-flight icing, turbulence, convective weather, cloud ceilings and visibilities. While traveling, one of the greatest annoyances is flight delays. Most flight delays are attributed to weather. Kulesa points out that the Aviation Weather Research Program’s National Convective Weather Forecast and Terminal Weather Forecast are improving the detection and forecasting of thunderstorms and thus minimalizing the numerous flight delays that we get due to stormy weather (Kulesa, 2004, p811). Another hazard that poses a severe threat to aviation is tornados. In the United States, tornado activities are at its peak between the months of May and June. It is crucial that we are able to detect this destructive force of nature. In a paper written by Steven V Vasiloff(2001), he discusses how the Terminal Doppler Weather Radar “dramatically improved remote detection of severe storms” (p861). Furthermore, Vasiloff illustrates how the Weather Surveillance Radar (WSR-88D) was able to forecast and detect a tornado in Salt Lake City 24 minutes before it started to form (p866). With technologies rapidly advancing, meteorological organizations are continuously their systems and forecasting models in order to provide the necessary weather information to those who need it, which in this case are pilots.
Rod Potts and Phillips G Gill (2014) of the Bureau of Meteorology highlights that due to growing computing power, a lot of progress was able to be made in probabilistic forecasting (p1).

During the planning process that a pilot goes through, he or she has to know what the forecasted weather is going to be at their destination. In the world of flying, a TAF (Terminal Aerodrome Forecast) is used in order to read what the forecasted conditions at that airport are. In a paper done by Judy E Ghirardelli and Bob Glahn (2010), they explain the improvements of the TAF by the Meteorological Development Laboratory:
In an effort to provide good quality aviation guidance for TAFs, MDL began development of a system to blend persistence with what could be deduced from existing numerical models run at the National Centers for Environmental Prediction (NCEP), and include an upstream component furnished by simple advective models. (p. 1028)
Another factor that poses a threat in everyday flying is ceilings and visibility. In order for a pilot to take off and land safely, the weather has to meet certain cloud ceiling and visibility requirements. This gets worse with the occurrence of precipitation. In an effort to further improve the forecasting capabilities and provide accurate information to the pilots, a research was by done by David E Rudack (2009) in order to see if the forecasting models can consistently provide the correct cloud ceiling and visibility with the onset of precipitation. The study found that 35% to 50% of the time it could have made the proper distinction of cloud ceilings and visibilities with the onset of precipitation (p. 936). On a more global scale, certain models are able to provide useful rainfall information. Daniel Vila (2010) reflects on how the SSM/I provides rainfall information. He goes over on how it is good at describing the global scale rainfall patterns and the annual and interannual variations of the patterns (1042).
It is well known that one of the contributing factors to making a flight uncomfortable is turbulence. In the world of flying there is a phenomena called Clear Air Turbulence (CAT). Essentially, it is a type of turbulence that cannot be detected due to a presence of bad weather. This is attributed to the characteristics of the earth’s Jetstream flow. In a research done by Gary P Ellrod and John A Kox (2010), they describe the improvements in the detection of Clear Air Turbulence and how cyclonic flow in the exit regions of strong jets were improved by using a Divergence Trend Term (DVT), resulting in a divergence modified turbulence index (797).
There are also different studies that proposed ideas on how to better understand the physics of the atmosphere and make better predictions of the atmospheric flow. By better understanding these occurrences, we can minimize the error in the forecasting of atmospheric conditions. P J Roebber and A Tsonis discuss the potential of reducing the errors in forecasting with help of certain mathematical models which can not only reduce these errors, but help uncover other errors that may lie underneath.Even with all these improvements, there are some areas where improvements can still be made. In an article written by A Makela and other contributors (2013), they point how the effects of Cold Season Thunderstorms still poses a threat to aviation safety in Finland. It was reported that on October 19th 2011, several airliners were struck by lightning during their approach or departure from Helsinki. Some pilots reported that the lightning reported momentary blindness and deafness. This of course is something that you wouldn’t want to happened, especially in such a critical phase of flight. Makela explains further that due to the rarity of the cold-season thunderstorms, it poses a greater safety issue to aviation. This phenomena still catches pilots and forecasters by surprise (856).
All in all, we are on the right track with weather detection for aviation. Thunderstorm forecasts are getting better, therefore minimizing airport delays. Tornado activities can easily be predicted with the use of the Doppler radar system. Thanks to the ongoing advances in computing, we are able to properly set up are models to make accurate predictions and giving pilots the necessary information that they need. Even though some areas still need improvements, the fortune tellers of the sky are a doing job keep the world of aviation safe.
References
Ellrod, G., & Knox, J. (2010). Improvements to an Operational Clear-Air Turbulence Diagnostic Index by Addition of a Divergence Trend Term. Weather and Forecasting, 25(2), 789-798
Ghirardelli, J., & Glahn, B. (2010). The Meteorological Development Laboratory’s Aviation Weather Prediction System. Weather and Forecasting, 1027-1051
Kulesa, G. (2014). IMPROVING AVIATION WEATHER FORECASTS: THE FEDERAL AVIATION ADMINISTRATION’S EFFORTS TO ENHANCE AIR TRAFFIC SAFETY AND EFFICIENCY. Bulletin of the American Meteorological Society, 811-813.
Mäkelä, A., Saltikoff, E., Julkunen, J., Juga, I., Gregow, E., & Niemelä, S. (2012). Cold Season Thunderstorms in Finland and Their Effect on Aviation Safety. Bulletin of the American Meteorological Society, 94(6), 848-858
Potts, R., & Gill, P. (2014). Developments in aviation meteorology. Meteorological Applications, 1-2
Roebber, P., & Tsonis, A. (2005). A Method to Improve Prediction of Atmospheric Flow Transitions. Journal of the Atmospheric Sciences, 62(10), 3818-3824.
Rudack, D. (2009). Aviation Weather Observations vs. LAMP Forecasts with the Onset of Precipitation. Bulletin of the American Meteorological Society, 929-938
Vila, D., Ferraro, R., & Semunegus, H. (2010). Improved Global Rainfall Retrieval Using the Special Sensor Microwave Imager (SSM/I). Journal of Applied Meteorology and Climatology,49(5), 1032-1043
Vasiloff, S. (2001). Improving Tornado Warnings with the Federal Aviation Administration's Terminal Doppler Weather Radar. Bulletin of the American Meteorological Society, 861-874.
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