a mash-up of mechanisms & nature
On the second day of February each year a vast cultural mechanism spins into gear as humanity pauses for a few minutes to celebrate the meteorological prognostication of a rodent. Groundhog day, according to various sources, traces its origins back to an odd sort of collision of culture, religion, dual calendar systems, and some pagan ritual mixed in for good measure. In modern incarnations, it involves a tongue-in-cheek reference on the morning radio to the various official shadow-spotters, and (if one is a true fan of the quasi-holiday) a re-watching of the Bill Murray feature film of the same name.
Predicting the weather (as the author has been not-so-subtly informed by personal conversations with actual human meteorologists) is hardly as simple as sky gazing. It continues to improve technologically, to be sure, with the expansion and use of vast satellite networks coupled to incredibly complex computer modeling systems harnessing the power of historical data and climate analysis. Yet, for all that technology, predicting the temperature a few days into the future is still mostly a blend of chance and educated guessing.
But why hasn’t humanity figured out the weather better than this?
It seems to be tied to three factors: (1) the Earth is big, (2) weather is smaller than folks generally think, and (3) the math is really, really, really, complex.
First, on the subjects of the Earth and the relatively small scale of weather, consider the local weather for a smallish city. Consider how small that city is on the scale of the whole planet, how insignificant that little smudge of urban population clustered around a river or another body of (climate-affecting) water. In the vastness of the whole planet, even a modestly-sized city is a mere speck of dust on the vast landscape.
Yet on the other hand, within that speck of dust there can be dozens or hundreds of smaller climates. The temperature in one neighborhood can easily vary from that of another. A storm may ravage a city block with hail over here, while a five minute walk away suburbanites are watering their lawns for lack of moisture. The fractaleqsue nature of nature implies that down to the smallest measurable space there is potential for variation to the next smallest measurable space.
It is a system that encompasses the whole of the planet, wherein every single molecule of air, moisture, dust and more matters… which leads to the other aspect of complexity: the math.
A mathematician could surely contribute to the understanding herein, speaking to modeling of chaotic systems and simultaneously accounting for a billion-billion variables by smoothing out the differences between them and averaging out errors and then speaking poetically of butterflies and wing-flapping metaphors. The simplicity of the complexity however is clear: to fully understand any system, the whole system needs to be understood. Thus, the more that is unknown about that system, the more that is estimated or smoothed out with averaging, the more (however subtle) uncertainty is added into that understanding. Across the impossibly long time-spans of days or weeks, impossibly long in face of the microsecond-long ticking of the changing weather models, that uncertainty is elevated from fractional speculation to flat out guesswork.
In other words, despite all our technology, the satellites, and data models which provide a darn good guess and can generally nudge the prognosticating prowess of modern meteorologists further than ever before in the history of humanity, in the end humans are likely still closer to being groundhogs than weather wizards.