Technology and Weather Prediction: A Sunny Future

By Joe Russo

As we enter the 21st century, a convergence of computer, communication and information technologies has made possible the generation of weather forecasts by machines alone. Sometimes referred to as a virtual meteorologist, mathematical models operating on powerful computers are beginning to mimic the skill level of a trained meteorologist. Like chess masters playing against computers, it is only a matter of time before computer models embody the knowledge and abilities of the best forecasters. However, computers do not eliminate the role of meteorologists; they redefine it. Instead of just forecasting, meteorologists interpret weather predictions for specific industries like agriculture, energy and golf.

Just like numerical weather prediction that started 50 years ago, the computer, along with communication and information technologies, is spawning the field of "weather application modelling." The model-assisted weather forecast interpretation supporting industry decision-making is nothing short of a revolution. Weather data users, such as golf course superintendents, no longer have to figure out how a temperature forecast is going to affect a degree-day accumulation or turf-related problems like crabgrass emergence.

Degree-days are the difference between the average daily temperature and some reference base, such as 10 Celsius (50 Fahrenheit). For example, if the average temperature is 13 C and the base is 10 C, there would be two degree-days computed for that day.

Accumulated degree-days are the sum of daily degree-days over some period; they are used to track the development of biological organisms, since their metabolism is more a function of temperature rather than the number of calendar days. Models analyze degree-day accumulation data for superintendents so they can better schedule irrigation and pesticide applications. The computer-generated interpretations are not only accurate, they are fast, reliable and consistent.

However, there are more components in this revolutionary picture than just models and computers. Automated weather stations are now not only cheaper, but are more compact. They can even communicate remotely with a desktop computer. In fact, sensors housed in cigar-size tubes can be placed just about anywhere in the environment to collect at minute intervals months of temperature data. Many stations come with software that can help a user interpret local weather observations.

Furthermore, the Internet permits users free access to weather data and forecasts through government, university and industry websites. The media now include television channels dedicated to weather, radio broadcasts focused on weather-related information, and satellite services bringing real-time radar imagery. Many of these weather sources partner with other technologies so irrigation systems can schedule their applications by receiving data from a nearby automated weather station.

In the weather application business, these competing technologies for bringing weather information to a user are grouped as "push, pull and plug." This simple categorization helps users appreciate the different kinds of information accessible. "Push" technologies focus on the end product, with little or no user input. It helps companies convey weather data to clients in a ready-to-use format. Electronic weather services, with their automatic delivery of weather information by e-mail or fax, are examples of push technology.

With "pull" technology, the goal is to allow users to customize the quantity and diversity of the information they receive. The idea is to give users as much access to information as possible. An Internet website is a good example of pull technology; users go online and pull weather data and forecasts off a website. "Plug" technologies enlist equipment for the generation and delivery of information to expand the types and intensity of local weather observations. An example of plug technology is an automated weather station; superintendents plug in the station locally and download weather data to software on a desktop computer.

Each competing technology group has its advantages and disadvantages. Automated weather stations provide local weather data but no forecasts. Internet websites are rich in general weather information but the data is not site specific and it takes considerable time to find and download it. Electronic weather services are fast, reliable, consistent and easy-to-use, but these advantages can be costly.

As this century unfolds, the future impact of technology on weather prediction can be extrapolated from current trends. In just the next few years, decision-making will become automated as models and equipment become better integrated. For example, irrigation equipment will turn itself on and off based on environmental monitoring and forecasts without the need of human intervention. As the number of satellites and their bandwidth increase in the upcoming years, users from just about any location will be able to view weather events and data on the Internet via a wireless, hand-held device such as a personal digital assistant (PDA). New computer visualization tools, using digital orthophoto as background, will soon allow superintendents to view photo-like images of frost pockets or likely spots of disease infections on their golf courses.

The most promising improvements to weather predictions are the long-range forecast models and the remote sensing of the ground environment. A better understanding of the long-term climate patterns will give rise to a new generation of long-range models. These models will provide forecasts of synoptic scale weather systems one to two years in advance of their observation. These predictions may be accurate enough for week-to-week decision-making. Such long-range forecasts could help superintendents schedule golf events or maintenance procedures.

In the next 10 years, advanced geostationary satellites will provide continuous cloud pattern imagery, remotely sensing weather variables at the surface and vertically throughout the atmosphere. Similarly positioned satellites will track natural resources on the earth's surface, such as fresh water. This satellite-borne data collection will be of a higher density and of a faster observation frequency than station networks on the surface. Furthermore, this data coverage will be for the entire earth. The combination of better global data and long-range forecast models will permit meteorologists to realistically track any future trend of global climate change.

Thanks to technology, the future of weather prediction looks sunny. People can expect weather forecasts and products to become more consistent in quality, more comprehensive in detail and more accessible both in terms of delivery and presentation.

Joe Russo is president and a senior research scientist at SkyBit, Inc., which developed the E- Weather Service for specific industries such as agriculture, energy and golf. He can be reached at (800) 454-2266.

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