It's a blog! Mainly of book reviews.
The author continues to show a poor grip on the principle of conservation of energy: It's all very well to say that energy cascades downward in scale from larger to smaller eddies in a turbulent flow, because the energy is still kinetic energy. When one gets to the scale where "viscous effects" are important we're back to the mysterious "destruction" of the energy. IT IS NOT DESTROYED! Where does it REALLY go? Heat. Which is to say, if you put a stick in a bucket of paint and stir it, then stop, the fluid swirls around for a bit, slowing down all the while, because of FRICTION ("viscous effects") which turns the bulk flow of the paint into random molecular motion of the paint - heat. So if you stir a fluid, ultimately you heat it up. The reason a river doesn't just stop flowing and stagnate is because gravitational potential energy is constantly being converted to kinetic energy of the water flow, at a rate at least as high as the rate at which viscosity is turning the flow kinetic energy into heat. If that isn't true what you have is - a lake!
Skipped the stuff on the geo-dynamo (origin of Earth's magnetic field) - interesting but not urgent. Alfven waves are qualitatively straight-forward; imagine plucking magnetic field lines like they are guitar strings! Of course the field must be embedded in a moving plasma. Magnetostrophic waves on the other hand, are clear as mud. They can occur when the magnetic field is rotating in relation to the plasma.
I read the first ~100p of this book. I stopped because the subject matter had diverged too far from my area of immediate interest (which was covered in the first chapter) rather than because the book is bad. In fact I think it is a good introduction to the topic for those with an interest and a background covering "normal" statistics to a level most STEM undergrads would have. Perhaps one thing that became obvious to me by inference should have been made explicit at the outset, which is that the fundamental general approach is as follows:
1. Get time series and plot it.
2. Guess any trends and/or periodicities in the data (various methods)
3. Subtract them (various methods)
4. Examine what's left ("residuals") to see if it behaves like noise (i.e. has some known type of random distribution) (various methods)
5. If it does, YAY! You have a usable model of the time series
6. If it does not, either make further guesses about trends/periodicities in the residuals and repeat from step 2 OR
7. Go back to the original time series and start from step 2 with different guesses about the nature of trends/periodicities
A flow chart of this at the beginning of the book would make what the book is actually about crystal clear.
As mentioned in a status update, the book does not assume the reader is scientifically motivated and does not discuss the meaning or validity of any trends, correlations or periodicities discovered. There are applications where this is entirely legitimate, probably the biggest and most utilised being analysis of financial/economic data for purposes of investment or trading: One only needs a model that works and not an explanation of why it works in order to make practical decisions. I would advise budding scientists to approach with caution, however; this form of analysis can only generate empirical models and hypotheses about why they are true are a separate but essential part of the scientific process. So, for example, if one discovers a model of the form, seasonal oscillation + white noise, describing your time series, one can make predictions about the future but there is no explanation of why the seasonal variation occurs. You are only part way there, scientifically.
A thorough grounding in basic "normal" statistics is required. An interesting observation is that the book (and the field) is not necessarily scientifically motivated; the presence of trends/periodicities/correlations may be detected or modeled but there is no discussion of whether or how they are causal or what they mean.
The presentation remains bad but I've just come across a possible explanation of the ionospheric phenomenon of "(magnetic) field-aligned irregularities."
The Gang, group portrait, June 2017.
Long John the Piratical Puppy and Jumble the Elephant. Also Rumble and Jumble.
So I was surprised when it was Venus, not Hymen who got peeved at Hero, but now we're having a lengthy digression involving the God of marriage...
Darwin's address: "H.M.S. Beagle, S. American Station."
Darwin had read Jane Austen and was an opera fan.