The Science of (Forecasting) Snow3rd March 2018
Predicting snow fall entails answering endless questions – When will it start or stop? Wow hard will it snow? What will be the ground and in the atmosphere temperatures? Will it rain, sleet or snow?
The key to forecasting relies on studying snow.
Although scientists have already learned a few things about snow properties, they continue to study it as it has far-reaching effects on regional weather patterns. Studying snow – its formation, distribution, changes over time, accumulation – is key to improving storm forecasting, arguably the most complicated things for forecasters to predict.
Forecasting snow is a challenge in the UK, mainly because there is often a very fine line between snow and rain. Changes as little as one tenth of a degree make the difference.
Snow, which can precipitate as snowflakes, graupel (opaque ice particles that form a soft, lumpy mass) or sleet (raindrops that freeze into small, translucent ice balls), is less likely to fall in urban areas as they usually have warmer surroundings.
Interestingly enough, snowflakes exhibit some of Earth’s most stunning natural fractal patterns (which have an infinite perimeter but a finite area); which are centred around a tiny mote of dust – ranging from volcanic ash to a particle from outer space.
Most precipitation starts as snow but, as it falls down, ends up melting into rain.
But how is weather forecast? Data is recollected in different points across the globe and through various means including nearly all large passenger airplanes which are equipped with automated weather instruments. Information on wind and air pressure as well as temperature is relayed to national weather stations. All data is, then, included in a 3D grid division of the atmosphere.
Using models (equations) based on the effects of wind direction and strength, barometric pressure, evaporation rates, Earth and atmosphere temperatures data is processed. The outcome, an estimation for each of the grid divisions, is subsequently computed in order to determine the effect of one region on neighbouring ones.
Although the models devised by generations of meteorologists are very complete, there are some misleading factors that throw off predictions: bad data, simplification of equations, and the existence of very small differences (sometimes considered to be negligible) that determine whether it rains or snows.