This series of Haby Hints looks at 10 difficult to forecast events or situations. Difficult to forecast means there is not a definite reliability of the forecast and the reliability is not as high as would be desired. This writing looks at the difficult situation of forecasting specifics.

A specific event narrows it down to a select time and place. For example, meeting for lunch at noon on a certain day at a particular restaurant is a specific event. It has been narrowed down to a specific time and place. In meteorology, this specificity is more generalized. For example, a forecast that gives a 70% chance of thunderstorms during the afternoon within a forecast city. The time frame is not for a specific time but rather covers a range of hours. A forecast city also will cover an area thus a forecast has to be made for citizens scattered across an area. The percentage is introduced since an event may or may not happen at the city within the given amount of time. Uncertainty is present in weather forecasts. Also, forecast reliability decreases with time. For example, a forecast for 5 days out is typically less reliable than a forecast for the next day. This occurs since small changes and small size phenomena are more likely to influence observed weather events as time advances (Butterfly Effect). It is more difficult to analyze phenomena as the size gets smaller, thus it is difficult to know how the extreme multitude a tiny phenomena will impact observed weather as time moves forward.

Why is it difficult to give a specific forecast? For example, a forecast for thunderstorms between 1:30 pm and 2:30 pm that is forecasted a day in advance. The reason is due to the enormous complexity of factors involved. Weather is influenced from all scales of motion and the properties at all these scales of motion cannot be analyzed. Enough information is gathered that a good general idea can be obtained for the expected weather. The amount of weather information gathered is limited by cost and feasibility. Since this gathered weather information is what is used to make the forecast, limitations on data gathering will limit forecasting ability. The ability to pinpoint exactly where a tornado will occur 3 hours in advance for example is not feasible. Too many factors limit being able to make this type of prediction. The good news is that forecasts will improve through greater computer power and data collection techniques. This improvement though will suffer from limitations on how much it can improve.