> For instance, the broad Australian accent (also called "Ocker"), which is more common in rural areas than metropolitan areas, has a prominent nasal twang and an emphasis on drawn-out long vowels. These characteristics are favourable for carrying over long, open distances with few obstructions. Rural accents in the U.S. exhibit similar adaptations.

My understanding agrees with other commenters in the thread - that there's no demonstrated connection between linguistic features and environment, and that connections like those are just intuited explanations rather than demonstrated scientific conclusions. Do you have a source you can cite for these?

The information is stored in DNA. Proteins are made based on the DNA sequence, and the shape of those proteins dictates their function. Like how tubulin makes microtubules and so on.

[removed]

This is a great description of what happens, but where are the instructions for all of this located? It's been explained to me that it's nothing but molecules bumping into each other but it sounds so complex it's hard to understand that.

The weather system is a complicated example of what's known as a chaotic system in mathematics. Most people have heard of the "butterfly effect", or the idea that a tiny perturbation of a system will exponentially grow into large-scale differences of behavior over time. This fundamentally limits our ability to predict the future with confidence.

An important parameter of any chaotic system is the Lyapunov time, which is the timescale over which perturbations grow large. The weather is a very complicated system, but current estimates for its Lyapunov time are around 15 days. Thus, any knowledge you have about particular weather conditions today won't inform your predictions very much for the weather in 15 days or so.

That being said, weather is driven by predictable factors like solar input, seasons, ocean currents, land topography, and so on. So at any given point on the Earth you can make some prediction of what the temperature, precipitation, and so on are likely to be on a given date, based on historical data. Those climate averages give you some degree of predictability.

So a way to think about it is:

• Weather forecasters are pretty good at telling you what will happen tomorrow.
• When they look out to 21 days from now, they can only predict based on historical climate data.
• Between "tomorrow" and "21 days from now", the accuracy of predictions gradually declines, because of chaos as well as limitations in the quality of our data and models.

[removed]

[removed]

This is how I understand your question:

If the average rain per month is X and for the first 2 weeks there have already have been X rain, does this mean that the rain probability for the next 2 weeks would be higher or lower?

There is no easy answer. There is no monthly rain quota where you used up your monthly rain early. One will have to analyze the reasons why there was more rain than usual.

Still, globally, I would be inclined to say that if the first part of the month was not normal, there is somewhat higher than average probability that the second won't be either. Weather patterns come from global cycles and global weather systems - and it in this case something is off. For example the European weather is highly influenced by the current state of the Azores High and the Icelandic Low. If these are off for some reason, it usually takes some time before they gradually return to normal.

[removed]

The centrosome in an interphase cell uses its radiating microtubules to sense the peripheries of the cell and place itself roughly in the center. Like pushing rods out in every direction to end up in the middle. During mitosis, the centrosome divides and each new baby centrosome does something similar, except they're also pushing each other away. So they end up towards each side of the cell.

The microtubules projecting from each centrosome each bind a chromatid at the other end, at the kinetochore (a big protein complex that sits on a particular sequence of DNA). Microtubules can bind on each side, so both centrosomes get connected to one side of the pair of sister chromatids. They can then do the same pushing thing, and since they're equally good at pushing, the chromatids all end up roughly at the mid-line of the cell. Then it's just a matter of cell cycle regulation - once everything is ready, the anaphase-promoting complex is activated, and activates separase to cleave the proteins holding the sister chromatids together. Then each centrosome can pull its set of chromosomes to its side of the cell in preparation for cytokinesis.

[removed]

[removed]

[removed]

To add to this, there are large-scale structures that DO make excellent predictors of weather to come. For instance, a "bomb cyclone" just hit the western coast of California. These mid-latitude cyclones follow somewhat predictable patterns.

Over the US, winds tend to blow from the west, especially along the Pacific coast, so it was pretty much guaranteed that this weather system would move from west to east. In that link you will see a satellite picture of the storm, which has the tell-tale cyclone shape, like a comma with two tails. The clouds on the western tail form a narrow band, which is indicative of the tall storm clouds associated with a cold front. The eastern tail is wide, made of low-hanging stratus clouds that form due to an incoming warm front. In the center of the comma is a swirling occluded front where the cold and warm fronts meet.

Experiencing a few days of little precipitation and overcast skies does not necessarily tell you a whole lot about the weather to come. But if you know that the large scale formation looks like this cyclone and you experience those overcast days followed by a couple clear days, then on the clear days you can bet that you are in the cloudless space between the comma tails, so the cold front is coming, bringing with it heavy rain.

But as HankScorpio here said, using monthly averages as a prediction tool is not a great idea, simply because of the potential variability of year-to-year climates.

[deleted]

This genuinely never came up in school even once, and I'm a chemical engineer! Very interesting concept, thank you! I'll edit my reply

It appears it would be useful for refrigeration or leak finding when combined with thermal imaging. Microleaks are extremely hard to detect even with leak detectors

haha yeah it's crazy thinking back and realising how many things we unquestionably believed, especially when younger, just because we were told.

The single best answer to your question should be, "It depends."

It's clear. It's succinct. It's complete.

You can, and should, find as many fields of weeds on this subject to get lost in as you can. And there are hundreds. Find some weeds and go play.

But you won't find a better answer. Sorry.

Anything with a negative jt coefficient will get colder when compressed, eg nitrogen and hydrogen over their relevant temperature ranges.

http://en.wikipedia.org/wiki/Joule-Thomson_coefficient

[removed]

[removed]

This is where we have to start thinking of weather in a probabilistic sense. How likely is an event to occur within the statistical framework of the recorded climate (official climate record is typically 30 years in the US)? This is where we get the things like 1000 year floods, 100 year heatwaves, etc. In the vast majority of weather systems, energy moves downscale. What I mean by this is that big weather systems driven by large scale processes then drive smaller systems which themselves drive even smaller ones. When two large scale events line up, like ENSO (el nino/la Nina) and typical winter time jet stream, you may see an event that is far outside the statistical norm within the climatological record.

So I guess we could say short term weather patterns can be connected together, but large scale and longer time scale patters will be more influential.

Lobotomized frogs are frogs too! :D

Thanks for letting me know. It’s funny – as I was writing that, I thought to myself, “I learned about this when I was quite young, not entirely sure it’s even accurate…”

[deleted]

[removed]