The forecast funnel model is an effective and systematic approach to weather forecasting. You will start your analysis at the global scale, then, like a funnel, narrow your focus down to the meso-scale. The amount of time you should spend analysing each scale is inversely proportional to the extent of the scale – spending only a little time analysing the global scale, and far more time analysing the meso-scale. The majority of your time should also be spent analysing the present weather to make a ‘now-cast’, with less time spent the further out you forecast. For short-term forecasts (0-6 hours), you may be able to rely more on extrapolation of weather observations, while long-range forecasts (e.g., 3 days) will involve NWP models to a much greater extent.
At the global scale, you will analyse the jet stream and determine how it will affect your area. For example, a strong South-Westerly flow will likely bring warm and moist air. It is very important to understand what is going on at the global scale before moving to smaller scales.
Questions to Ask:
To answer these questions, you can use satellite imagery and upper-air analysis charts. The water vapour image is particularly good at highlighting the flow pattern. The 250hPa and 500hPa charts show troughs and ridges being guided along the jet streams.
Troughs and ridges will either be stationary, progressive, or retrogressive. A stationary pattern is when the troughs and ridges remain in the same pace over several days or longer. A progressive pattern is when the troughs and ridges evolve from West to East. If a system is retrogressive, the jet stream (longwave) undergoes a discontinuous East to West movement whereby an existing trough weakens and moves eastwards. As the trough retrogresses, an upstream shortwave will strongly deepen, developing into a stationary longwave trough West of the original longwave trough position. Discontinuous retrogression is usually associated with strong development of cyclonic circulation (cyclogenesis) as the upstream shortwave intensifies.
Tools to Use:
At the synoptic scale, you will analyse the locations of low- and high-pressure centres, and frontal systems.
Questions to Ask:
Determining the Problem of the Day: It is important to relate the various weather features of the synoptic scale to the global scale, and determine if they will affect your forecast area.
After this is done, it is important to check the quality of the NWPs you intend to use. This can be quickly accomplished by comparing satellite and other observation data with the initial panels of the model runs.
Next, the evolution of the features of interest need to be considered. NWPs are the main tools to do this.
Finally, armed with this information, the forecaster will likely have a good perspective of the general problems of the day, including the confidence level of the forecast evolution.
Tools to Use:
At the mesoscale, you will determine how the local topography will affect your problem of the day.
Questions to Ask:
Most weather forecasts begin with a statement about the general weather pattern. Then it should include key information about weather factors that influence snow instability. This includes information about temperature and freezing level, precipitation (type and amount), and ridgetop winds. In short-term forecasts, you may be able to provide specific values and ranges, or in long-term forecasts only very general statements in the trends of overall weather patterns, temperatures, and precipitations. A good weather forecast should also include a statement about confidence. This is an opportunity for the forecaster to express their degree of certainty in their weather forecast. Forecast confidence is affected by a number of different factors, including:
The tools used to forecast are dependent on the range of the forecast. A short-range forecast (6-12 hours) can rely primarily on a method of extrapolating the existing conditions. The forecast parameters in this case can be very specific and detailed. On the other hand, a long-range forecast (5-14 days) relies on computer models and statistical climatological models.
0 – 6hrs. Essentially nowcasting with a heavy reliance on extrapolation
6 – 12hrs. Equal reliance on extrapolation and NWP models
12 – 48hrs. Increasing reliance on NWP models and increasing generality of forecast.
3 – 4 days. Nearly complete reliance on NWP models, with very general temperature and precipitation statements.
5 – 14 days. Decreasing reliance on computer models, increasing reliance on statistical and ensemble models.