AI Prompts Example

Query text:

Use the well-known meme "Meteorologists always predict the weather accurately. They're only wrong about the location or time." (© by Valery Shmelev)  1994

Write a serious note in the style of a "scientific" experiment, statistical sample, or observational data, substantiating this meme. An example of the style of the article is given below in quotation marks:

"The cluster SPT2349-56 was first noticed in 2010 in data from the South Pole Telescope in Antarctica. It is an extremely dense system containing over thirty galaxies, where new stars are being formed 1,000 times more actively than in the Milky Way. Gravity within such a structure enhances the interactions between galaxies and the gas between them, leading to an increase in the energy and temperature of this gas. However, new data obtained using the ALMA radio telescope network have shown that the temperature of the gas within the cluster exceeds 10 million Kelvin, which is approximately five times higher than expected for such an early cosmic era. Gravity alone would not have been able to heat the gas to such a temperature—this would only be possible in the modern universe.
The cause of such a high temperature remains a subject of debate, but scientists hypothesize that the additional energy came from powerful jets emanating from three or more more supermassive black holes within the cluster. This additional energy could have significantly "superheated" the environment earlier than standard models of galaxy structure formation allowed. This phenomenon suggests that the interaction between active black holes, star formation processes, and the environment within clusters plays a more important role in the early Universe than previously thought.

The example discusses a completely different topic. But use the sentiment from it.

AI response:

An observational study of weather forecast accuracy under spatiotemporal uncertainty
During a long-term monitoring of meteorological forecasts conducted in the European part of Russia from 2018 to 2025, a systematic agreement between meteorologists' predicted atmospheric phenomena and actual weather conditions was recorded—albeit with a significant shift in the spatial or temporal coordinate. An analysis of a sample of over 12,000 daily forecasts from three leading meteorological services revealed the following pattern: in 89.4% of cases, the predicted event (rain, snow, thunderstorm, heatwave, or cold snap) actually occurred, but either in a different region (with a probability of 52.1%) or on a different day (with a probability of 47.3%). In 15.6% of cases, shifts were observed for both parameters simultaneously.
Interestingly, the average spatial shift was 320 ± 85 km, which correlates with the characteristic wavelength of mesoscale atmospheric waves involved in air mass transport. The temporal shift, in turn, exhibited a normal distribution with a mode of 24 hours and a standard deviation of ± 18 hours, consistent with the typical speed of cyclonic systems over temperate latitudes. The highest accuracy (in terms of the coincidence of phenomenon, location, and time) was observed under stationary anticyclones—however, such situations accounted for less than 7% of all observations. In the remaining cases, model forecasts demonstrated "predictive reliability in content," but not in coordinates. This suggests that modern numerical atmospheric models accurately reproduce the physics of meteorological processes, but experience systematic difficulties in localizing them in time and space due to their high sensitivity to initial conditions (the so-called "butterfly effect" in meteorology).
Thus, we can conclude: meteorologists do indeed predict the weather with a high degree of reliability—but the reliability domain should be interpreted as a spatiotemporal volume, not a specific point. In this sense, the famous remark of Valery Shmelev (© by Valery Shmelev)—"Meteorologists always accurately predict the weather." "They're only mistaken about place or time"—it turns out not to be ironic, but an empirically substantiated consequence of the nonlinear dynamics of the atmosphere.

AI Processing:   https://chat.qwen.ai/s/t_8380558d-0ad4-4977-b2a3-47575f49518a?fev=0.1.31

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